title
stringlengths 8
189
| detail_url
stringlengths 27
45
| author_list
sequencelengths 0
28
| abstract
stringlengths 0
403
|
|---|---|---|---|
Learning Multi-step Robotic Manipulation Policies from Visual Observation of Scene and Q-value Predictions of Previous Action | https://ieeexplore.ieee.org/document/9812251/ | [
"Sulabh Kumra",
"Shirin Joshi",
"Ferat Sahin",
"Sulabh Kumra",
"Shirin Joshi",
"Ferat Sahin"
] | In this work, we focus on multi-step manipulation tasks that involve long-horizon planning and considers progress reversal. Such tasks interlace high-level reasoning that consists of the expected states that can be attained to achieve an overall task and low-level reasoning that decides what actions will yield these states. We propose a sample efficient Previous Action Conditioned Robotic Manipula... |
ReorientBot: Learning Object Reorientation for Specific-Posed Placement | https://ieeexplore.ieee.org/document/9811881/ | [
"Kentaro Wada",
"Stephen James",
"Andrew J. Davison",
"Kentaro Wada",
"Stephen James",
"Andrew J. Davison"
] | Robots need the capability of placing objects in arbitrary, specific poses to rearrange the world and achieve various valuable tasks. Object reorientation plays a crucial role in this as objects may not initially be oriented such that the robot can grasp and then immediately place them in a specific goal pose. In this work, we present a vision-based manipulation system, ReorientBot, which consists... |
LEGS: Learning Efficient Grasp Sets for Exploratory Grasping | https://ieeexplore.ieee.org/document/9812138/ | [
"Letian Fu",
"Michael Danielczuk",
"Ashwin Balakrishna",
"Daniel S. Brown",
"Jeffrey Ichnowski",
"Eugen Solowjow",
"Ken Goldberg",
"Letian Fu",
"Michael Danielczuk",
"Ashwin Balakrishna",
"Daniel S. Brown",
"Jeffrey Ichnowski",
"Eugen Solowjow",
"Ken Goldberg"
] | While deep learning has enabled significant progress in designing general purpose robot grasping systems, there remain objects which still pose challenges for these systems. Recent work on Exploratory Grasping has formalized the problem of systematically exploring grasps on these adversarial objects and explored a multi-armed bandit model for identifying high-quality grasps on each object stable p... |
Learning Latent Graph Dynamics for Visual Manipulation of Deformable Objects | https://ieeexplore.ieee.org/document/9811597/ | [
"Xiao Ma",
"David Hsu",
"Wee Sun Lee",
"Xiao Ma",
"David Hsu",
"Wee Sun Lee"
] | Manipulating deformable objects, such as ropes and clothing, is a long-standing challenge in robotics, because of their large degrees of freedom, complex non-linear dynamics, and self-occlusion in visual perception. The key difficulty is a suitable representation, rich enough to capture the object shape, dynamics for manipulation and yet simple enough to be estimated reliably from visual observati... |
Learning Visual Shape Control of Novel 3D Deformable Objects from Partial-View Point Clouds | https://ieeexplore.ieee.org/document/9812215/ | [
"Bao Thach",
"Brian Y. Cho",
"Alan Kuntz",
"Tucker Hermans",
"Bao Thach",
"Brian Y. Cho",
"Alan Kuntz",
"Tucker Hermans"
] | If robots could reliably manipulate the shape of 3D deformable objects, they could find applications in fields ranging from home care to warehouse fulfillment to surgical assistance. Analytic models of elastic, 3D deformable objects require numerous parameters to describe the potentially infinite degrees of freedom present in determining the object's shape. Previous attempts at performing 3D shape... |
Real2Sim2Real: Self-Supervised Learning of Physical Single-Step Dynamic Actions for Planar Robot Casting | https://ieeexplore.ieee.org/document/9811651/ | [
"Vincent Lim",
"Huang Huang",
"Lawrence Yunliang Chen",
"Jonathan Wang",
"Jeffrey Ichnowski",
"Daniel Seita",
"Michael Laskey",
"Ken Goldberg",
"Vincent Lim",
"Huang Huang",
"Lawrence Yunliang Chen",
"Jonathan Wang",
"Jeffrey Ichnowski",
"Daniel Seita",
"Michael Laskey",
"Ken Goldberg"
] | This paper introduces the task of Planar Robot Casting (PRC): where one planar motion of a robot arm holding one end of a cable causes the other end to slide across the plane toward a desired target. PRC allows the cable to reach points beyond the robot workspace and has applications for cable management in homes, warehouses, and factories. To efficiently learn a PRC policy for a given cable, we p... |
Cluttered Food Grasping with Adaptive Fingers and Synthetic-Data Trained Object Detection | https://ieeexplore.ieee.org/document/9812448/ | [
"Avinash Ummadisingu",
"Kuniyuki Takahashi",
"Naoki Fukaya",
"Avinash Ummadisingu",
"Kuniyuki Takahashi",
"Naoki Fukaya"
] | The food packaging industry handles an immense variety of food products with wide-ranging shapes and sizes, even within one kind of food. Menus are also diverse and change frequently, making automation of pick-and-place difficult. A popular approach to bin-picking is to first identify each piece of food in the tray by using an instance segmentation method. However, human annotations to train these... |
Visuotactile-RL: Learning Multimodal Manipulation Policies with Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/9812019/ | [
"Johanna Hansen",
"Francois Hogan",
"Dmitriy Rivkin",
"David Meger",
"Michael Jenkin",
"Gregory Dudek",
"Johanna Hansen",
"Francois Hogan",
"Dmitriy Rivkin",
"David Meger",
"Michael Jenkin",
"Gregory Dudek"
] | Manipulating objects with dexterity requires timely feedback that simultaneously leverages the senses of vision and touch. In this paper, we focus on the problem setting where both visual and tactile sensors provide pixel-level feedback for Visuotactile reinforcement learning agents. We investigate the challenges associated with multimodal learning and propose several improvements to existing RL m... |
Reducing Tactile Sim2Real Domain Gaps via Deep Texture Generation Networks | https://ieeexplore.ieee.org/document/9811801/ | [
"Tudor Jianu",
"Daniel Fernandes Gomes",
"Shan Luo",
"Tudor Jianu",
"Daniel Fernandes Gomes",
"Shan Luo"
] | Recently simulation methods have been developed for optical tactile sensors to enable the Sim2Real learning, i.e., first training models in simulation before deploying them on a real robot. However, some artefacts in real objects are unpredictable, such as imperfections caused by fabrication processes, or scratches by natural wear and tear, and thus cannot be represented in the simulation, resulti... |
Grasp Pose Selection Under Region Constraints for Dirty Dish Grasps Based on Inference of Grasp Success Probability through Self-Supervised Learning | https://ieeexplore.ieee.org/document/9812084/ | [
"Shumpei Wakabayashi",
"Shingo Kitagawa",
"Kento Kawaharazuka",
"Takayuki Murooka",
"Kei Okada",
"Masayuki Inaba",
"Shumpei Wakabayashi",
"Shingo Kitagawa",
"Kento Kawaharazuka",
"Takayuki Murooka",
"Kei Okada",
"Masayuki Inaba"
] | In the literature on object grasping, the robot often determines the grasp point and posture from visual information. They predict the grasping point uniquely from the object's shape characteristics. However, as a practical matter, there are cases where there are constraints on grasp point due to the object states, the limitation of the robot's hardware and the surrounding environment. In this stu... |
Constrained Variable Impedance Control using Quadratic Programming | https://ieeexplore.ieee.org/document/9812210/ | [
"Zhehao Jin",
"Dongdong Qin",
"Andong Liu",
"Wen-An Zhang",
"Li Yu",
"Zhehao Jin",
"Dongdong Qin",
"Andong Liu",
"Wen-An Zhang",
"Li Yu"
] | This paper proposes a quadratic programming (QP)-based variable impedance control (VIC) algorithm to solve contact-rich trajectory tracking problems with impedance, position and velocity constraints. To the best of our knowledge, the impedance constraints which are significant to ensure the worst contact compliance have never been considered in other previous works. To handle the impedance constra... |
Variable Stiffness Control via External Torque Estimation Using LSTM | https://ieeexplore.ieee.org/document/9811955/ | [
"Jaesug Jung",
"Seungbin You",
"Donghyeon Kim",
"Jaeheung Park",
"Jaesug Jung",
"Seungbin You",
"Donghyeon Kim",
"Jaeheung Park"
] | Stable contact and safe responses to the collision have been studied to develop interactive robots such as service and collaborative robots. Stable and safe interactions are usually achieved through the inherent compliance of a motion controller with external torque estimation. However, a fixed control gain would sacrifice either compliance or position tracking performance. Additionally, external ... |
Mixed Control for Whole-Body Compliance of a Humanoid Robot | https://ieeexplore.ieee.org/document/9812196/ | [
"Xiaozhu Ju",
"Jiajun Wang",
"Gang Han",
"Mingguo Zhao",
"Xiaozhu Ju",
"Jiajun Wang",
"Gang Han",
"Mingguo Zhao"
] | The hierarchical quadratic programming (HQP) is commonly applied to consider strict hierarchies of multi-tasks and robot's physical inequality constraints during whole-body compliance. However, for the one-step HQP, the solution can oscillate when it is close to the boundary of constraints. It is because the abrupt hit of the bounds gives rise to unrealizable jerks and even infeasible solutions. T... |
A Memory-based SO(3) Parameterization: Theory and Application to 6D Impedance Control with Radially Unbounded Potential Function | https://ieeexplore.ieee.org/document/9812268/ | [
"Jinyeong Jeong",
"Hrishik Mishra",
"Christian Ott",
"Min Jun Kim",
"Jinyeong Jeong",
"Hrishik Mishra",
"Christian Ott",
"Min Jun Kim"
] | This paper proposes a parameterization method to represent SO (3) over multiple turns. This method is called a memory-based parameterization, because the idea is to integrate the past trajectory of exponential coordinates. The parameterization is consistent in the sense that the true rotation matrix can be reconstructed by using the exponential map. As an application of the proposed method, a 6D i... |
A model free robot control method for dragging an object on a planar surface by applying top contact forces | https://ieeexplore.ieee.org/document/9811686/ | [
"Savvas Sampaziotis",
"Zoe Doulgeri",
"Savvas Sampaziotis",
"Zoe Doulgeri"
] | In this work, a robot control method is proposed for dragging an object by applying top contact forces under unknown friction and object dynamics. This is a non-prehensile manipulation of an object that can enhance the grasping capabilities of a robotic manipulator in a plethora of grasping scenarios. In the proposed method, an initializing controller generates reference contact force trajectories... |
Unfreezing Social Navigation: Dynamical Systems based Compliance for Contact Control in Robot Navigation | https://ieeexplore.ieee.org/document/9811772/ | [
"Diego Paez-Granados",
"Vaibhav Gupta",
"Aude Billard",
"Diego Paez-Granados",
"Vaibhav Gupta",
"Aude Billard"
] | Large efforts have focused on ensuring that the controllers for mobile service robots follow proxemics and other social rules to ensure both safe and socially acceptable distance to pedestrians. Nonetheless, involuntary contact may be unavoidable when the robot travels in crowded areas or when encountering adversarial pedestrians. Freezing the robot in response to contact might be detrimental to b... |
Easing Reliance on Collision-free Planning with Contact-aware Control | https://ieeexplore.ieee.org/document/9811631/ | [
"Tao Pang",
"Russ Tedrake",
"Tao Pang",
"Russ Tedrake"
] | We believe that the future of robot motion planning will look very different than how it looks today: instead of complex collision avoidance trajectories with a brittle dependence on sensing and estimation of the environment, motion plans should consist of smooth, simple trajectories and be executed by robots that are not afraid of making contact. Here we present a “contact-aware” controller which... |
Autonomous Ultrasound Scanning using Bayesian Optimization and Hybrid Force Control | https://ieeexplore.ieee.org/document/9812410/ | [
"Raghavv Goel",
"Fnu Abhimanyu",
"Kirtan Patel",
"John Galeotti",
"Howie Choset",
"Raghavv Goel",
"Fnu Abhimanyu",
"Kirtan Patel",
"John Galeotti",
"Howie Choset"
] | Ultrasound scanning is an imaging technique that aids medical professionals in diagnostics and interventional procedures. However, a trained human-in-the-loop (HITL) with a radiologist is required to perform the scanning procedure. We seek to create a novel ultrasound system that can provide imaging in the absence of a trained radiologist, say for patients in the field who suffered injuries after ... |
Trajectory Prediction for Autonomous Driving with Topometric Map | https://ieeexplore.ieee.org/document/9811712/ | [
"Jiaolong Xu",
"Liang Xiao",
"Dawei Zhao",
"Yiming Nie",
"Bin Dai",
"Jiaolong Xu",
"Liang Xiao",
"Dawei Zhao",
"Yiming Nie",
"Bin Dai"
] | State-of-the-art autonomous driving systems rely on high definition (HD) maps for localization and navigation. However, building and maintaining HD maps is time-consuming and expensive. Furthermore, the HD maps assume structured environment such as the existence of major road and lanes, which are not present in rural areas. In this work, we propose an end-to-end transformer networks based approach... |
See Yourself in Others: Attending Multiple Tasks for Own Failure Detection | https://ieeexplore.ieee.org/document/9812310/ | [
"Boyang Sun",
"Jiaxu Xing",
"Hermann Blum",
"Roland Siegwart",
"Cesar Cadena",
"Boyang Sun",
"Jiaxu Xing",
"Hermann Blum",
"Roland Siegwart",
"Cesar Cadena"
] | Autonomous robots deal with unexpected scenarios in real environments. Given input images, various visual perception tasks can be performed, e.g., semantic segmentation, depth estimation and normal estimation. These different tasks provide rich information for the whole robotic perception system. All tasks have their own characteristics while sharing some latent correlations. However, some of the ... |
I Know What You Draw: Learning Grasp Detection Conditioned on a Few Freehand Sketches | https://ieeexplore.ieee.org/document/9812372/ | [
"Haitao Lin",
"Chilam Cheang",
"Yanwei Fu",
"Xiangyang Xue",
"Haitao Lin",
"Chilam Cheang",
"Yanwei Fu",
"Xiangyang Xue"
] | In this paper, we are interested in the problem of generating target grasps by understanding freehand sketches. The sketch is useful for the persons who cannot formulate language and the cases where a textual description is not available on the fly. However, very few works are aware of the usability of this novel interactive way between humans and robots. To this end, we propose a method to genera... |
Implicit LiDAR Network: LiDAR Super-Resolution via Interpolation Weight Prediction | https://ieeexplore.ieee.org/document/9811992/ | [
"Youngsun Kwon",
"Minhyuk Sung",
"Sung–Eui Yoon",
"Youngsun Kwon",
"Minhyuk Sung",
"Sung–Eui Yoon"
] | Super-resolution of LiDAR range images is crucial to improving many downstream tasks such as object detection, recognition, and tracking. While deep learning has made a remarkable advances in super-resolution techniques, typical convolutional architectures limit upscaling factors to specific output resolutions in training. Recent work has shown that a continuous representation of an image and lear... |
Incremental Few-Shot Object Detection for Robotics | https://ieeexplore.ieee.org/document/9811856/ | [
"Yiting Li",
"Haiyue Zhu",
"Sichao Tian",
"Fan Feng",
"Jun Ma",
"Chek Sing Teo",
"Cheng Xiang",
"Prahlad Vadakkepat",
"Tong Heng Lee",
"Yiting Li",
"Haiyue Zhu",
"Sichao Tian",
"Fan Feng",
"Jun Ma",
"Chek Sing Teo",
"Cheng Xiang",
"Prahlad Vadakkepat",
"Tong Heng Lee"
] | Incremental few-shot learning is highly expected for practical robotics applications. On one hand, robot is desired to learn new tasks quickly and flexibly using only few annotated training samples; on the other hand, such new additional tasks should be learned in a continuous and incremental manner without forgetting the previous learned knowledge dramatically. In this work, we propose a novel Cl... |
CLA-NeRF: Category-Level Articulated Neural Radiance Field | https://ieeexplore.ieee.org/document/9812272/ | [
"Wei-Cheng Tseng",
"Hung-Ju Liao",
"Lin Yen-Chen",
"Min Sun",
"Wei-Cheng Tseng",
"Hung-Ju Liao",
"Lin Yen-Chen",
"Min Sun"
] | We propose CLA-NeRF - a Category-Level Articulated Neural Radiance Field that can perform view synthesis, part segmentation, and articulated pose estimation. CLA-NeRF is trained at the object category level using no CAD models and no depth, but a set of RGB images with ground truth camera poses and part segments. During inference, it only takes a few RGB views (i.e., few-shot) of an unseen 3D obje... |
Learning to Infer Kinematic Hierarchies for Novel Object Instances | https://ieeexplore.ieee.org/document/9811968/ | [
"Hameed Abdul-Rashid",
"Miles Freeman",
"Ben Abbatematteo",
"George Konidaris",
"Daniel Ritchie",
"Hameed Abdul-Rashid",
"Miles Freeman",
"Ben Abbatematteo",
"George Konidaris",
"Daniel Ritchie"
] | Manipulating an articulated object requires perceiving its kinematic hierarchy: its parts, how each can move, and how those motions are coupled. Previous work has explored perception for kinematics, but none infers a complete kinematic hierarchy on never-before-seen object instances, without relying on a schema or template. We present a novel perception system that achieves this goal. Our system i... |
Self-Supervised Camera Self-Calibration from Video | https://ieeexplore.ieee.org/document/9811784/ | [
"Jiading Fang",
"Igor Vasiljevic",
"Vitor Guizilini",
"Rares Ambrus",
"Greg Shakhnarovich",
"Adrien Gaidon",
"Matthew R. Walter",
"Jiading Fang",
"Igor Vasiljevic",
"Vitor Guizilini",
"Rares Ambrus",
"Greg Shakhnarovich",
"Adrien Gaidon",
"Matthew R. Walter"
] | Camera calibration is integral to robotics and computer vision algorithms that seek to infer geometric properties of the scene from visual input streams. In practice, calibration is a laborious procedure requiring specialized data collection and careful tuning. This process must be repeated whenever the parameters of the camera change, which can be a frequent occurrence for mobile robots and auton... |
Learning 6-DoF Object Poses to Grasp Category-Level Objects by Language Instructions | https://ieeexplore.ieee.org/document/9811367/ | [
"Chilam Cheang",
"Haitao Lin",
"Yanwei Fu",
"Xiangyang Xue",
"Chilam Cheang",
"Haitao Lin",
"Yanwei Fu",
"Xiangyang Xue"
] | This paper studies the task of any objects grasping from the known categories by free-form language instructions. This task demands the technique in computer vision, natural language processing, and robotics. We bring these disciplines together on this open challenge, which is essential to human-robot interaction. Critically, the key challenge lies in inferring the category of objects from linguis... |
Multiple Consistency Supervision based Semi-supervised OCT Segmentation using Very Limited Annotations | https://ieeexplore.ieee.org/document/9812447/ | [
"Ye Lu",
"Yutian Shen",
"Xiaohan Xing",
"Max Q.-H. Meng",
"Ye Lu",
"Yutian Shen",
"Xiaohan Xing",
"Max Q.-H. Meng"
] | Optical Coherence Tomography (OCT) is a rapidly growing and promising imaging technique, enabling non-invasive high-resolution visualization of biological tissues. Segmentation of tissue structures from OCT scans is essen-tial for disease diagnosis but remains challenging for the blurry boundaries and large volumes. Deep learning-based OCT segmentation algorithms always require large numbers of an... |
Decoupling of Inertia Effect in Angular Momentum of a Humanoid and its Application to Resolved Viscoelasticity Control | https://ieeexplore.ieee.org/document/9811692/ | [
"Zewen He",
"Ko Yamamoto",
"Zewen He",
"Ko Yamamoto"
] | As a basic part of the centroidal dynamics, an-gular momentum plays a critical role in humanoid motion control. Therefore, how to explicitly express and control an-gular momentum through whole-body motion is an important topic for researchers. This study discusses the selection of the generalized velocity corresponding to whole-body angular momentum. Based on the discussion, we present a method th... |
Using Eye Gaze to Forecast Human Pose in Everyday Pick and Place Actions | https://ieeexplore.ieee.org/document/9812079/ | [
"Haziq Razali",
"Yiannis Demiris",
"Haziq Razali",
"Yiannis Demiris"
] | Collaborative robots that operate alongside humans require the ability to understand their intent and forecast their pose. Among the various indicators of intent, the eye gaze is particularly important as it signals action towards the gazed object. By observing a person's gaze, one can effectively predict the object of interest and subsequently, forecast the person's pose. We leverage this and pre... |
On the Reliability of Inverse Optimal Control | https://ieeexplore.ieee.org/document/9811847/ | [
"Jessica Colombel",
"David Daney",
"François Charpillet",
"Jessica Colombel",
"David Daney",
"François Charpillet"
] | Inverse Optimal Control (IOC) is a popular method for human motion analysis. In the context of these methods it is necessary to pay attention to the reliability of the results. This paper proposes an approach based on the evaluation of Karush-Kuhn-Tucker conditions relying on a complete analysis with Singular Value Decomposition and provides a detailed analysis of reliability. With respect to a gr... |
DanceHAT: Generate Stable Dances for Humanoid Robots with Adversarial Training | https://ieeexplore.ieee.org/document/9811649/ | [
"Buqing Nie",
"Yue Gao",
"Buqing Nie",
"Yue Gao"
] | Music to dance for humanoid robots is an interesting task. Robot dance generation is challenging when considering music pieces, human dancer motions, and robot stability simultaneously. Previous methods rely on human-designed motion library or stability constraints for robot postures. Hence, dance generation for humanoid robots requires expert design, which can be time-consuming across different h... |
Design and Development for Humanoid-Vehicle Transformer Platform with Plastic Resin Structure and Distributed Redundant Sensors | https://ieeexplore.ieee.org/document/9811683/ | [
"Tasuku Makabe",
"Naoki Hiraoka",
"Shintaro Noda",
"Tomoki Anzai",
"Kohei Kimura",
"Mirai Hattori",
"Hiroya Sato",
"Fumihito Sugai",
"Yohei Kakiuchi",
"Kei Okada",
"Masayuki Inaba",
"Tasuku Makabe",
"Naoki Hiraoka",
"Shintaro Noda",
"Tomoki Anzai",
"Kohei Kimura",
"Mirai Hattori",
"Hiroya Sato",
"Fumihito Sugai",
"Yohei Kakiuchi",
"Kei Okada",
"Masayuki Inaba"
] | The humanoid robot that can transform itself into a form according to its purpose requires whole-body motions with complex contact state transitions such as recovery from a fall and transition to the target form. To make the robot behavior in simulations closer to that in the real world for planning complex target trajectories, we need a platform that can measure the body stiffness during the moti... |
A Robotic Lower Limb With Eight DoFs and Whole-Foot Tactile Perception for Anthropomorphic Behavior Performance | https://ieeexplore.ieee.org/document/9811690/ | [
"Funing Hou",
"Jixiao Liu",
"Kuo Liu",
"Dicai Chen",
"Shijie Guo",
"Funing Hou",
"Jixiao Liu",
"Kuo Liu",
"Dicai Chen",
"Shijie Guo"
] | Humanoid lower limbs with tactile cognition are crucial for future bipedal robots developing advanced bionic intelligence, such as owning autonomous reflexes and performing human-like actions. Most existing robotic lower limbs focus on providing physical support and mobility, with little work on more bionic DoFs or tactile sensing abilities that are more than significant for a fully humanoid syste... |
Introducing RH5 Manus: A Powerful Humanoid Upper Body Design for Dynamic Movements | https://ieeexplore.ieee.org/document/9811843/ | [
"Melya Boukheddimi",
"Shivesh Kumar",
"Heiner Peters",
"Dennis Mronga",
"Rohan Budhiraja",
"Frank Kirchner",
"Melya Boukheddimi",
"Shivesh Kumar",
"Heiner Peters",
"Dennis Mronga",
"Rohan Budhiraja",
"Frank Kirchner"
] | It is well established that a stiff structure along with an optimal mass distribution are key features to perform dynamic movements, and parallel designs provide these characteristics to a robot. This work presents the new upper-body design of the humanoid robot RH5 named RH5 Manus with series-parallel hybrid design. The new design choices allow us to perform dynamic motions including tasks that i... |
Design and Control of a Miniature Bipedal Robot with Proprioceptive Actuation for Dynamic Behaviors | https://ieeexplore.ieee.org/document/9811790/ | [
"Yeting Liu",
"Junjie Shen",
"Jingwen Zhang",
"Xiaoguang Zhang",
"Taoyuanmin Zhu",
"Dennis Hong",
"Yeting Liu",
"Junjie Shen",
"Jingwen Zhang",
"Xiaoguang Zhang",
"Taoyuanmin Zhu",
"Dennis Hong"
] | As the study of humanoid robots becomes a world-wide interdisciplinary research field, the demand for a cost-effective bipedal robot system capable of dynamic behaviors is growing exponentially. This paper presents a miniature bipedal robot named Bipedal Robot Unit with Compliance Enhanced (BRUCE). Each leg of BRUCE has five degrees of freedom (DoFs), which includes a spherical hip joint, a knee j... |
Human Navigational Intent Inference with Probabilistic and Optimal Approaches | https://ieeexplore.ieee.org/document/9811883/ | [
"Pedram Agand",
"Mahdi Taherahmadi",
"Angelica Lim",
"Mo Chen",
"Pedram Agand",
"Mahdi Taherahmadi",
"Angelica Lim",
"Mo Chen"
] | Although human navigational intent inference has been studied in the literature, none have adequately considered both the dynamics that describe human motion and internal human parameters that may affect human navigational behaviour. In this paper, we propose a general probabilistic framework to infer the probability distribution over future navigational states of a human. Our framework incorporat... |
Watch and Learn: Learning to control feedback linearizable systems from expert demonstrations | https://ieeexplore.ieee.org/document/9812054/ | [
"Alimzhan Sultangazin",
"Luigi Pannocchi",
"Lucas Fraile",
"Paulo Tabuada",
"Alimzhan Sultangazin",
"Luigi Pannocchi",
"Lucas Fraile",
"Paulo Tabuada"
] | In this paper, we revisit the problem of learning a stabilizing controller from a finite number of demonstrations by an expert. By focusing on feedback linearizable systems, we show how to combine expert demonstrations into a stabilizing controller, provided that demonstrations are sufficiently long and there are at least $n+1$ of them, where $n$ is the number of states of the system being control... |
Attentive One-Shot Meta-Imitation Learning From Visual Demonstration | https://ieeexplore.ieee.org/document/9812281/ | [
"Vishal Bhutani",
"Anima Majumder",
"Madhu Vankadari",
"Samrat Dutta",
"Aaditya Asati",
"Swagat Kumar",
"Vishal Bhutani",
"Anima Majumder",
"Madhu Vankadari",
"Samrat Dutta",
"Aaditya Asati",
"Swagat Kumar"
] | The ability to apply a previously-learned skill (e.g., pushing) to a new task (context or object) is an important requirement for new-age robots. An attempt is made to solve this problem in this paper by proposing a deep meta-imitation learning framework comprising of an attentive-embedding net-work and a control network, capable of learning a new task in an end-to-end manner while requiring only ... |
Learning Sensorimotor Primitives of Sequential Manipulation Tasks from Visual Demonstrations | https://ieeexplore.ieee.org/document/9811703/ | [
"Junchi Liang",
"Bowen Wen",
"Kostas Bekris",
"Abdeslam Boularias",
"Junchi Liang",
"Bowen Wen",
"Kostas Bekris",
"Abdeslam Boularias"
] | This work aims to learn how to perform complex robot manipulation tasks that are composed of several, consecutively executed low-level sub-tasks, given as input a few visual demonstrations of the tasks performed by a person. The sub-tasks consist of moving the robot's end-effector until it reaches a sub-goal region in the task space, performing an action, and triggering the next sub-task when a pr... |
Maximum Likelihood Constraint Inference on Continuous State Spaces | https://ieeexplore.ieee.org/document/9811705/ | [
"Kaylene C. Stocking",
"D. Livingston McPherson",
"Robert P. Matthew",
"Claire J. Tomlin",
"Kaylene C. Stocking",
"D. Livingston McPherson",
"Robert P. Matthew",
"Claire J. Tomlin"
] | When a robot observes another agent unexpectedly modifying their behavior, inferring the most likely cause is a valuable tool for maintaining safety and reacting appropriately. In this work, we present a novel method for inferring constraints that works on continuous, possibly sub-optimal demonstrations. We first learn a representation of the continuous-state maximum entropy trajectory distributio... |
Learning Stable Dynamical Systems for Visual Servoing | https://ieeexplore.ieee.org/document/9811944/ | [
"Antonio Paolillo",
"Matteo Saveriano",
"Antonio Paolillo",
"Matteo Saveriano"
] | This work presents the dual benefit of integrating imitation learning techniques, based on the dynamical systems formalism, with the visual servoing paradigm. On the one hand, dynamical systems allow to program additional skills without explicitly coding them in the visual servoing law, but leveraging few demonstrations of the full desired behavior. On the other, visual servoing allows to consider... |
Robot Skill Adaptation via Soft Actor-Critic Gaussian Mixture Models | https://ieeexplore.ieee.org/document/9811770/ | [
"Iman Nematollahi",
"Erick Rosete-Beas",
"Adrian Röfer",
"Tim Welschehold",
"Abhinav Valada",
"Wolfram Burgard",
"Iman Nematollahi",
"Erick Rosete-Beas",
"Adrian Röfer",
"Tim Welschehold",
"Abhinav Valada",
"Wolfram Burgard"
] | $A$ core challenge for an autonomous agent acting in the real world is to adapt its repertoire of skills to cope with its noisy perception and dynamics. To scale learning of skills to long-horizon tasks, robots should be able to learn and later refine their skills in a structured manner through trajectories rather than making instantaneous decisions individually at each time step. To this end, we ... |
Abnormal Occupancy Grid Map Recognition using Attention Network | https://ieeexplore.ieee.org/document/9812106/ | [
"Fuqin Deng",
"Hua Feng",
"Mingjian Liang",
"Qi Feng",
"Ningbo Yi",
"Yong Yang",
"Yuan Gao",
"Junfeng Chen",
"Tin Lun Lam",
"Fuqin Deng",
"Hua Feng",
"Mingjian Liang",
"Qi Feng",
"Ningbo Yi",
"Yong Yang",
"Yuan Gao",
"Junfeng Chen",
"Tin Lun Lam"
] | The occupancy grid map is a critical component of autonomous positioning and navigation in the mobile robotic system, as many other systems' performance depends heavily on it. To guarantee the quality of the occupancy grid maps, researchers previously had to perform tedious manual recognition for a long time. This work focuses on automatic abnormal occupancy grid map recognition using the residual... |
Uncertainty from Motion for DNN Monocular Depth Estimation | https://ieeexplore.ieee.org/document/9812222/ | [
"Soumya Sudhakar",
"Vivienne Sze",
"Sertac Karaman",
"Soumya Sudhakar",
"Vivienne Sze",
"Sertac Karaman"
] | Deployment of deep neural networks (DNNs) for monocular depth estimation in safety-critical scenarios on resource-constrained platforms requires well-calibrated and efficient uncertainty estimates. However, many popular uncertainty estimation techniques, including state-of-the-art ensembles and popular sampling-based methods, require multiple inferences per input, making them difficult to deploy i... |
Depth Completion Using Geometry-Aware Embedding | https://ieeexplore.ieee.org/document/9811556/ | [
"Wenchao du",
"Hu Chen",
"Hongyu Yang",
"Yi Zhang",
"Wenchao du",
"Hu Chen",
"Hongyu Yang",
"Yi Zhang"
] | Exploiting internal spatial geometric constraints of sparse LiDARs is beneficial to depth completion, however, has been not explored well. This paper proposes an efficient method to learn geometry-aware embedding, which encodes the local and global geometric structure information from 3D points, e.g., scene layout, object's sizes and shapes, to guide dense depth estimation. Specifically, we utiliz... |
Prediction of Depth Camera Missing Measurements Using Deep Learning for Next Best View Planning | https://ieeexplore.ieee.org/document/9812358/ | [
"Riccardo Monica",
"Jacopo Aleotti",
"Riccardo Monica",
"Jacopo Aleotti"
] | Depth images usually contain pixels with invalid measurements. This paper presents a deep learning approach that receives as input a partially-known volumetric model of the environment and a camera pose, and it predicts the probability that a pixel would contain a valid depth measurement if a camera was placed at the given pose. The proposed network architecture consists of a 3D Convolutional Neur... |
Message Passing Framework for Vision Prediction Stability in Human Robot Interaction | https://ieeexplore.ieee.org/document/9812439/ | [
"Youngkyoon Jang",
"Yiannis Demiris",
"Youngkyoon Jang",
"Yiannis Demiris"
] | In Human Robot Interaction (HRI) scenarios, robot systems would benefit from an understanding of the user's state, actions and their effects on the environments to enable better interactions. While there are specialised vision algorithms for different perceptual channels, such as objects, scenes, human pose, and human actions, it is worth considering how their interaction can help improve each oth... |
Unsupervised Depth Completion and Denoising for RGB-D Sensors | https://ieeexplore.ieee.org/document/9812392/ | [
"Lei Fan",
"Yunxuan Li",
"Chen Jiang",
"Ying Wu",
"Lei Fan",
"Yunxuan Li",
"Chen Jiang",
"Ying Wu"
] | Depth information is considered valuable as it describes geometric structures, which benefits various robotic tasks. However, the depth acquired by RGB-D sensors still suffers from two deficiencies, i.e., incompletion and noises. Previous methods complete depth by exploring hand-tuned models or raising surface assumptions, while nowadays, deep approaches intend to solve this problem with rendered ... |
PA-AWCNN: Two-stream Parallel Attention Adaptive Weight Network for RGB-D Action Recognition | https://ieeexplore.ieee.org/document/9811995/ | [
"Lu Yao",
"Sheng Liu",
"Chaonan Li",
"Siyu Zou",
"Shengyong Chen",
"Diyi Guan",
"Lu Yao",
"Sheng Liu",
"Chaonan Li",
"Siyu Zou",
"Shengyong Chen",
"Diyi Guan"
] | Due to overly relying on appearance information or adopting direct static feature fusion, most of the existing action recognition methods based on multi-modality have poor robustness and insufficient consideration of modality differences. To address these problems, we propose a two-stream adaptive weight integration network with a three-dimensional parallel attention module, PA-AWCNN. Firstly, a t... |
Variable Rate Compression for Raw 3D Point Clouds | https://ieeexplore.ieee.org/document/9812239/ | [
"Md Ahmed Al Muzaddid",
"William J. Beksi",
"Md Ahmed Al Muzaddid",
"William J. Beksi"
] | In this paper, we propose a novel variable rate deep compression architecture that operates on raw 3D point cloud data. The majority of learning-based point cloud compression methods work on a downsampled representation of the data. Moreover, many existing techniques require training multiple networks for different compression rates to generate consolidated point clouds of varying quality. In cont... |
Stable and Efficient Shapley Value-Based Reward Reallocation for Multi-Agent Reinforcement Learning of Autonomous Vehicles | https://ieeexplore.ieee.org/document/9811626/ | [
"Songyang Han",
"He Wang",
"Sanbao Su",
"Yuanyuan Shi",
"Fei Miao",
"Songyang Han",
"He Wang",
"Sanbao Su",
"Yuanyuan Shi",
"Fei Miao"
] | With the development of sensing and communication technologies in networked cyber-physical systems (CPSs), multi-agent reinforcement learning (MARL)-based methodologies are integrated into the control process of physical systems and demonstrate prominent performance in a wide array of CPS domains, such as connected autonomous vehicles (CAVs). However, it remains challenging to mathematically chara... |
A Framework for Real-World Multi-Robot Systems Running Decentralized GNN-Based Policies | https://ieeexplore.ieee.org/document/9811744/ | [
"Jan Blumenkamp",
"Steven Morad",
"Jennifer Gielis",
"Qingbiao Li",
"Amanda Prorok",
"Jan Blumenkamp",
"Steven Morad",
"Jennifer Gielis",
"Qingbiao Li",
"Amanda Prorok"
] | Graph Neural Networks (GNNs) are a paradigm-shifting neural architecture to facilitate the learning of complex multi-agent behaviors. Recent work has demonstrated remarkable performance in tasks such as flocking, multi-agent path planning and cooperative coverage. However, the policies derived through GNN-based learning schemes have not yet been deployed to the real-world on physical multi-robot s... |
Coverage Control in Multi-Robot Systems via Graph Neural Networks | https://ieeexplore.ieee.org/document/9811854/ | [
"Walker Gosrich",
"Siddharth Mayya",
"Rebecca Li",
"James Paulos",
"Mark Yim",
"Alejandro Ribeiro",
"Vijay Kumar",
"Walker Gosrich",
"Siddharth Mayya",
"Rebecca Li",
"James Paulos",
"Mark Yim",
"Alejandro Ribeiro",
"Vijay Kumar"
] | This paper develops a decentralized approach to mobile sensor coverage by a multi-robot system. We consider a scenario where a team of robots with limited sensing range must position itself to effectively detect events of interest in a region characterized by areas of varying importance. Towards this end, we develop a decentralized control policy for the robots-realized via a Graph Neural Network-... |
Multi-Target Encirclement with Collision Avoidance via Deep Reinforcement Learning using Relational Graphs | https://ieeexplore.ieee.org/document/9812151/ | [
"Tianle Zhang",
"Zhen Liu",
"Zhiqiang Pu",
"Jianqiang Yi",
"Tianle Zhang",
"Zhen Liu",
"Zhiqiang Pu",
"Jianqiang Yi"
] | In this paper, we propose a novel decentralized method based on deep reinforcement learning using robot-level and target-level relational graphs, to solve the problem of multi-target encirclement with collision avoidance (MECA). Specifically, the robot-level relational graphs, composed of three heterogeneous relational graphs between each robot and other robots, targets and obstacles, are modeled ... |
Decentralized Global Connectivity Maintenance for Multi-Robot Navigation: A Reinforcement Learning Approach | https://ieeexplore.ieee.org/document/9812163/ | [
"Minghao Li",
"Yingrui Jie",
"Yang Kong",
"Hui Cheng",
"Minghao Li",
"Yingrui Jie",
"Yang Kong",
"Hui Cheng"
] | The problem of multi-robot navigation of connectivity maintenance is challenging in multi-robot applications. This work investigates how to navigate a multi-robot team in unknown environments while maintaining connectivity. We propose a reinforcement learning (RL) approach to develop a decentralized policy, which is shared among multiple robots. Given range sensor measurements and the positions of... |
Multi-robot Cooperative Pursuit via Potential Field-Enhanced Reinforcement Learning | https://ieeexplore.ieee.org/document/9812083/ | [
"Zheng Zhang",
"Xiaohan Wang",
"Qingrui Zhang",
"Tianjiang Hu",
"Zheng Zhang",
"Xiaohan Wang",
"Qingrui Zhang",
"Tianjiang Hu"
] | It is of great challenge, though promising, to coordinate collective robots for hunting an evader in a decentralized manner purely in light of local observations. In this paper, this challenge is addressed by a novel hybrid cooperative pursuit algorithm that combines reinforcement learning with the artificial potential field method. In the proposed algorithm, decentralized deep reinforcement learn... |
Learning Scalable Policies over Graphs for Multi-Robot Task Allocation using Capsule Attention Networks | https://ieeexplore.ieee.org/document/9812370/ | [
"Steve Paul",
"Payam Ghassemi",
"Souma Chowdhury",
"Steve Paul",
"Payam Ghassemi",
"Souma Chowdhury"
] | This paper presents a novel graph reinforcement learning (RL) architecture to solve multi-robot task allocation (MRTA) problems that involve tasks with deadlines and workload, and robot constraints such as work capacity. While drawing motivation from recent graph learning methods that learn to solve combinatorial optimization (CO) problems such as multi-Traveling Salesman and Vehicle Routing Probl... |
Task Allocation with Load Management in Multi-Agent Teams | https://ieeexplore.ieee.org/document/9811374/ | [
"Haochen Wu",
"Amin Ghadami",
"Alparslan Emrah Bayrak",
"Jonathon M. Smereka",
"Bogdan I. Epureanu",
"Haochen Wu",
"Amin Ghadami",
"Alparslan Emrah Bayrak",
"Jonathon M. Smereka",
"Bogdan I. Epureanu"
] | In operations of multi-agent teams ranging from homogeneous robot swarms to heterogeneous human-autonomy teams, unexpected events might occur. While efficiency of operation for multi-agent task allocation problems is the primary objective, it is essential that the decision-making framework is intelligent enough to manage unexpected task load with limited resources. Otherwise, operation effectivene... |
The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark Towards Physically Realistic Embodied AI | https://ieeexplore.ieee.org/document/9812329/ | [
"Chuang Gan",
"Siyuan Zhou",
"Jeremy Schwartz",
"Seth Alter",
"Abhishek Bhandwaldar",
"Dan Gutfreund",
"Daniel L.K. Yamins",
"James J. DiCarlo",
"Josh McDermott",
"Antonio Torralba",
"Joshua B. Tenenbaum",
"Chuang Gan",
"Siyuan Zhou",
"Jeremy Schwartz",
"Seth Alter",
"Abhishek Bhandwaldar",
"Dan Gutfreund",
"Daniel L.K. Yamins",
"James J. DiCarlo",
"Josh McDermott",
"Antonio Torralba",
"Joshua B. Tenenbaum"
] | We introduce a visually-guided task-and-motion planning benchmark, which we call the ThreeDWorld Trans-port Challenge. In this challenge, an embodied agent is spawned randomly in a simulated physical home environment and required to transport a small set of objects scattered around the house with containers. We build this benchmark challenge using the ThreeDWorld simulation: a virtual 3D environme... |
Online Adaptive Identification and Switching of Soft Contact Model Based on ART-II Method | https://ieeexplore.ieee.org/document/9811740/ | [
"Yi Liu",
"Di Wu",
"Fengtao Han",
"Jing Guo",
"Zhaoshui He",
"Chao Liu",
"Yi Liu",
"Di Wu",
"Fengtao Han",
"Jing Guo",
"Zhaoshui He",
"Chao Liu"
] | In order to obtain a high-precision contact model that can properly describe the target soft tissue, this paper proposes a hybrid soft contact model based on a clustering algorithm ART-II, which selects the most suitable soft contact model according to the surgical environment. The least-square method is used to identify the parameters of the model online. In the experiments, different parts of an... |
A Proprioceptive Haptic Device Design for Teaching Bimanual Manipulation | https://ieeexplore.ieee.org/document/9811694/ | [
"Choongin Lee",
"Taeyoon Lee",
"Jae-Kyung Min",
"Albert Wang",
"SungPyo Lee",
"Jaesung Oh",
"Chang-Woo Park",
"Keunjun Choi",
"Choongin Lee",
"Taeyoon Lee",
"Jae-Kyung Min",
"Albert Wang",
"SungPyo Lee",
"Jaesung Oh",
"Chang-Woo Park",
"Keunjun Choi"
] | Manipulation involves a broad spectrum of skills, e.g., polishing, peeling, flipping, screwing, etc., requiring complex and delicate control over both force and position. This paper aims at designing an optimal haptic interface for providing a robot with direct demonstrations of human's innate intelligence in performing a wide range of force-based bimanual manipulation tasks. Based on the proprioc... |
A Wearable Fingertip Cutaneous Haptic Device with Continuous Omnidirectional Motion Feedback | https://ieeexplore.ieee.org/document/9812131/ | [
"Peizhi Zhang",
"Mitsuhiro Kamezaki",
"Yutaro Hattori",
"Shigeki Sugano",
"Peizhi Zhang",
"Mitsuhiro Kamezaki",
"Yutaro Hattori",
"Shigeki Sugano"
] | In both teleoperation in real space and exploration in virtual space, ‘passive’ and ‘active’ haptic feedback can help to improve the performance of the task, especially in object handover and exploring. However, the current wearable haptic devices are hard to display continuous omnidirectional motion feedback simultaneously, which makes it not yet achieved. In this study, we thus propose a cutaneo... |
Rendering Virtual Inertia in Haptic Interfaces: Analysis and Limitations | https://ieeexplore.ieee.org/document/9812207/ | [
"Jorge Juan Gil",
"Axier Ugartemendia",
"Iñaki Díaz",
"Jorge Juan Gil",
"Axier Ugartemendia",
"Iñaki Díaz"
] | Virtual environments designed for haptic applications are usually rendered as a combination of spring and damper elements. The resulting haptic experience can be greatly enhanced by also adding virtual inertia, for example when interacting with mobile virtual objects. This paper analyzes the impact of implementing virtual inertia on haptic rendering stability. It describes the methodology followed... |
Interactive Robotic Grasping with Attribute-Guided Disambiguation | https://ieeexplore.ieee.org/document/9812360/ | [
"Yang Yang",
"Xibai Lou",
"Changhyun Choi",
"Yang Yang",
"Xibai Lou",
"Changhyun Choi"
] | Interactive robotic grasping using natural language is one of the most fundamental tasks in human-robot interaction. However, language can be a source of ambiguity, particularly when there are ambiguous visual or linguistic contents. This paper investigates the use of object attributes in disambiguation and develops an interactive grasping system capable of effectively resolving ambiguities via di... |
Autonomous Exploration Development Environment and the Planning Algorithms | https://ieeexplore.ieee.org/document/9812330/ | [
"Chao Cao",
"Hongbiao Zhu",
"Fan Yang",
"Yukun Xia",
"Howie Choset",
"Jean Oh",
"Ji Zhang",
"Chao Cao",
"Hongbiao Zhu",
"Fan Yang",
"Yukun Xia",
"Howie Choset",
"Jean Oh",
"Ji Zhang"
] | Autonomous Exploration Development Environment is an open-source repository released to facilitate development of high-level planning algorithms and integration of com-plete autonomous navigation systems. The repository contains representative simulation environment models, fundamental navigation modules, e.g., local planner, terrain traversability analysis, waypoint following, and visualization t... |
Event-Triggered Tracking Control Scheme for Quadrotors with External Disturbances: Theory and Validations | https://ieeexplore.ieee.org/document/9812326/ | [
"Pengcheng Gao",
"Gang Wang",
"Yunfeng Ji",
"Qingdu Li",
"Jianwei Zhang",
"Yantao Shen",
"Peng Li",
"Pengcheng Gao",
"Gang Wang",
"Yunfeng Ji",
"Qingdu Li",
"Jianwei Zhang",
"Yantao Shen",
"Peng Li"
] | This article studies the tracking control of a quadrotor unmanned aerial vehicle (UAV) under time-varying external disturbances. An event-triggered sliding mode control (SMC) strategy is proposed by introducing a new triggering condition form of desired trajectory, quadrotor position, and velocity. In the sense of Lyapunov theory, the stability of the entire closed-loop control system is analyzed,... |
PredictionNet: Real-Time Joint Probabilistic Traffic Prediction for Planning, Control, and Simulation | https://ieeexplore.ieee.org/document/9812223/ | [
"Alexey Kamenev",
"Lirui Wang",
"Ollin Boer Bohan",
"Ishwar Kulkarni",
"Bilal Kartal",
"Artem Molchanov",
"Stan Birchfield",
"David Nistér",
"Nikolai Smolyanskiy",
"Alexey Kamenev",
"Lirui Wang",
"Ollin Boer Bohan",
"Ishwar Kulkarni",
"Bilal Kartal",
"Artem Molchanov",
"Stan Birchfield",
"David Nistér",
"Nikolai Smolyanskiy"
] | Predicting the future motion of traffic agents is crucial for safe and efficient autonomous driving. To this end, we present PredictionNet, a deep neural network (DNN) that predicts the motion of all surrounding traffic agents together with the ego-vehicle's motion. All predictions are probabilistic and are represented in a simple top-down rasterization that allows an arbitrary number of agents. C... |
Graph Neural Network Based Relation Learning for Abnormal Perception Information Detection in Self-Driving Scenarios | https://ieeexplore.ieee.org/document/9812411/ | [
"Kefan Jin",
"Hongye Wang",
"Changxing Liu",
"Yu Zhai",
"Ling Tang",
"Kefan Jin",
"Hongye Wang",
"Changxing Liu",
"Yu Zhai",
"Ling Tang"
] | Robustness and safety concerns of perception systems are of great importance for autonomous vehicle navigation applications. Recent researches demonstrate that the surrounding dynamic object detection results of current perception systems can be easily interfered or attacked to mislead the navigation performance of the victim vehicle. In this paper, we develop a GNN based relation learning network... |
Domain Generalization for Vision-based Driving Trajectory Generation | https://ieeexplore.ieee.org/document/9812070/ | [
"Yunkai Wang",
"Dongkun Zhang",
"Yuxiang Cui",
"Zexi Chen",
"Wei Jing",
"Junbo Chen",
"Rong Xiong",
"Yue Wang",
"Yunkai Wang",
"Dongkun Zhang",
"Yuxiang Cui",
"Zexi Chen",
"Wei Jing",
"Junbo Chen",
"Rong Xiong",
"Yue Wang"
] | One of the challenges in vision-based driving trajectory generation is dealing with out-of-distribution scenarios. In this paper, we propose a domain generalization method for vision-based driving trajectory generation for autonomous vehicles in urban environments, which can be seen as a solution to extend the Invariant Risk Minimization (IRM) method in complex problems. We leverage an adversarial... |
StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving | https://ieeexplore.ieee.org/document/9811830/ | [
"Jinkyu Kim",
"Reza Mahjourian",
"Scott Ettinger",
"Mayank Bansal",
"Brandyn White",
"Ben Sapp",
"Dragomir Anguelov",
"Jinkyu Kim",
"Reza Mahjourian",
"Scott Ettinger",
"Mayank Bansal",
"Brandyn White",
"Ben Sapp",
"Dragomir Anguelov"
] | We introduce a motion forecasting (behavior prediction) method that meets the latency requirements for autonomous driving in dense urban environments without sacrificing accuracy. A whole-scene sparse input representation allows StopNet to scale to predicting trajectories for hundreds of road agents with reliable latency. In addition to predicting trajectories, our scene encoder lends itself to pr... |
FusionNet: Coarse-to-Fine Extrinsic Calibration Network of LiDAR and Camera with Hierarchical Point-pixel Fusion | https://ieeexplore.ieee.org/document/9811945/ | [
"Guangming Wang",
"Jiahao Qiu",
"Yanfeng Guo",
"Hesheng Wang",
"Guangming Wang",
"Jiahao Qiu",
"Yanfeng Guo",
"Hesheng Wang"
] | In this paper, we propose a novel network, Fusion-Net, which can estimate the extrinsic calibration matrix between LiDAR and a monocular RGB camera with high accuracy and robustness. FusionNet is a coarse-to-fine method, providing an online and end-to-end solution that can automatically detect and correct the decalibration without any specially designed targets or environments. First, the network ... |
Cyclops: Open Platform for Scale Truck Platooning | https://ieeexplore.ieee.org/document/9812174/ | [
"Hyeongyu Lee",
"Jaegeun Park",
"Changjin Koo",
"Jong-Chan Kim",
"Yongsoon Eun",
"Hyeongyu Lee",
"Jaegeun Park",
"Changjin Koo",
"Jong-Chan Kim",
"Yongsoon Eun"
] | Cyclops, introduced in this paper, is an open research platform for everyone who wants to validate novel ideas and approaches in self-driving heavy-duty vehicle platooning. The platform consists of multiple 1/14 scale semi-trailer trucks equipped with associated computing, communication and control modules that enable self-driving on our scale proving ground. The perception system for each vehicle... |
Runtime Safety Assurance for Learning-enabled Control of Autonomous Driving Vehicles | https://ieeexplore.ieee.org/document/9812177/ | [
"Shengduo Chen",
"Yaowei Sun",
"Dachuan Li",
"Qiang Wang",
"Qi Hao",
"Joseph Sifakis",
"Shengduo Chen",
"Yaowei Sun",
"Dachuan Li",
"Qiang Wang",
"Qi Hao",
"Joseph Sifakis"
] | Providing safety guarantees for Autonomous Vehicle (AV) systems with machine-learning based controllers remains a challenging issue. In this work, we propose Simplex-Drive, a framework that can achieve runtime safety assurance for machine-learning enabled controllers of AVs. The proposed Simplex-Drive consists of an unverified Deep Reinforcement Learning (DRL)-based advanced controller (AC) that a... |
Looking for Trouble: Informative Planning for Safe Trajectories with Occlusions | https://ieeexplore.ieee.org/document/9811994/ | [
"Barry Gilhuly",
"Armin Sadeghi",
"Peyman Yedmellat",
"Kasra Rezaee",
"Stephen L. Smith",
"Barry Gilhuly",
"Armin Sadeghi",
"Peyman Yedmellat",
"Kasra Rezaee",
"Stephen L. Smith"
] | Planning a safe trajectory for an ego vehicle through an environment with occluded regions is a challenging task. Existing methods use some combination of metrics to evaluate a trajectory, either taking a worst case view or allowing for some probabilistic estimate, to eliminate or minimize the risk of collision respectively. Typically, these approaches assume occluded regions of the environment ar... |
A Deep Concept Graph Network for Interaction-Aware Trajectory Prediction | https://ieeexplore.ieee.org/document/9811567/ | [
"Yutong Ban",
"Xiao Li",
"Guy Rosman",
"Igor Gilitschenski",
"Ozanan Meireles",
"Sertac Karaman",
"Daniela Rus",
"Yutong Ban",
"Xiao Li",
"Guy Rosman",
"Igor Gilitschenski",
"Ozanan Meireles",
"Sertac Karaman",
"Daniela Rus"
] | Temporal patterns (how vehicles behave in our observed past) underline our reasoning of how people drive on the road, and can explain why we make certain predictions about interactions among road agents. In this paper we propose the ConceptNet trajectory predictor - a novel prediction framework that is able to incorporate agent interactions as explicit edges in a temporal knowledge graph. We demon... |
Real-Time Trajectory Planning for Autonomous Driving with Gaussian Process and Incremental Refinement | https://ieeexplore.ieee.org/document/9812405/ | [
"Jie Cheng",
"Yingbing Chen",
"Qingwen Zhang",
"Lu Gan",
"Chengju Liu",
"Ming Liu",
"Jie Cheng",
"Yingbing Chen",
"Qingwen Zhang",
"Lu Gan",
"Chengju Liu",
"Ming Liu"
] | Real-time kinodynamic trajectory planning in dy-namic environments is critical yet challenging for autonomous driving. In this paper, we propose an efficient trajectory plan-ning system for autonomous driving in complex dynamic sce-narios through iterative and incremental path-speed optimization. Exploiting the decoupled structure of the planning prob-lem, a path planner based on Gaussian process ... |
Scalable Gradient Ascent for Controllers in Constrained POMDPs | https://ieeexplore.ieee.org/document/9812262/ | [
"Kyle Hollins Wray",
"Kenneth Czuprynski",
"Kyle Hollins Wray",
"Kenneth Czuprynski"
] | This paper presents a novel gradient ascent al-gorithm and nonlinear programming algorithm for finite state controller policies in constrained partially observable Markov decision processes (CPOMDPs). A key component of the gradient ascent algorithm is a constraint projection to ensure constraints are satisfied. Both an optimal and an approximate projection are formally defined. A theoretical anal... |
A Model Predictive-based Motion Planning Method for Safe and Agile Traversal of Unknown and Occluding Environments | https://ieeexplore.ieee.org/document/9811717/ | [
"Jacob Higgins",
"Nicola Bezzo",
"Jacob Higgins",
"Nicola Bezzo"
] | Agile navigation through uncertain and obstacle-rich environments remains a challenging task for autonomous mobile robots (AMR). For most AMR, obstacles are identified using onboard sensors, e.g., lidar or cameras. The effectiveness of these sensors may be severely limited, however, by occlusions introduced from the presence of other obstacles. The occluded area may contain obstacles, static or dy... |
GOHOME: Graph-Oriented Heatmap Output for future Motion Estimation | https://ieeexplore.ieee.org/document/9812253/ | [
"Thomas Gilles",
"Stefano Sabatini",
"Dzmitry Tsishkou",
"Bogdan Stanciulescu",
"Fabien Moutarde",
"Thomas Gilles",
"Stefano Sabatini",
"Dzmitry Tsishkou",
"Bogdan Stanciulescu",
"Fabien Moutarde"
] | In this paper, we propose GOHOME, a method leveraging graph representations of the High Definition Map and sparse projections to generate a heatmap output representing the future position probability distribution for a given agent in a traffic scene. This heatmap output yields an unconstrained 2D grid representation of agent future possible locations, allowing inherent multimodality and a measure ... |
Translating Images into Maps | https://ieeexplore.ieee.org/document/9811901/ | [
"Avishkar Saha",
"Oscar Mendez",
"Chris Russell",
"Richard Bowden",
"Avishkar Saha",
"Oscar Mendez",
"Chris Russell",
"Richard Bowden"
] | We approach instantaneous mapping, converting images to a top-down view of the world, as a translation problem. We show how a novel form of transformer network can be used to map from images and video directly to an overhead map or bird's-eye-view (BEV) of the world, in a single end-to-end network. We assume a 1–1 correspondence between a vertical scanline in the image, and rays passing through th... |
SMAC-Seg: LiDAR Panoptic Segmentation via Sparse Multi-directional Attention Clustering | https://ieeexplore.ieee.org/document/9812408/ | [
"Enxu Li",
"Ryan Razani",
"Yixuan Xu",
"Bingbing Liu",
"Enxu Li",
"Ryan Razani",
"Yixuan Xu",
"Bingbing Liu"
] | Panoptic segmentation aims to address semantic and instance segmentation simultaneously in a unified framework. However, an efficient solution of panoptic segmentation in applications like autonomous driving is still an open research problem. In this work, we propose a novel LiDAR-based panoptic system, called SMAC-Seg. We present a learnable sparse multi-directional attention clustering to segmen... |
Superpoint-guided Semi-supervised Semantic Segmentation of 3D Point Clouds | https://ieeexplore.ieee.org/document/9811904/ | [
"Shuang Deng",
"Qiulei Dong",
"Bo Liu",
"Zhanyi Hu",
"Shuang Deng",
"Qiulei Dong",
"Bo Liu",
"Zhanyi Hu"
] | 3D point cloud semantic segmentation is a challenging topic in the computer vision field. Most of the existing methods in literature require a large amount of fully labeled training data, but it is extremely time-consuming to obtain these training data by manually labeling massive point clouds. Addressing this problem, we propose a superpoint-guided semi-supervised segmentation network for 3D poin... |
Efficient and Robust Semantic Mapping for Indoor Environments | https://ieeexplore.ieee.org/document/9812205/ | [
"Daniel Seichter",
"Patrick Langer",
"Tim Wengefeld",
"Benjamin Lewandowski",
"Dominik Höchemer",
"Horst-Michael Gross",
"Daniel Seichter",
"Patrick Langer",
"Tim Wengefeld",
"Benjamin Lewandowski",
"Dominik Höchemer",
"Horst-Michael Gross"
] | A key proficiency an autonomous mobile robot must have to perform high-level tasks is a strong understanding of its environment. This involves information about what types of objects are present, where they are, what their spatial extend is, and how they can be reached, i.e., information about free space is also crucial. Semantic maps are a powerful instrument providing such information. However, ... |
Towards Broad Learning Networks on Unmanned Mobile Robot for Semantic Segmentation | https://ieeexplore.ieee.org/document/9812204/ | [
"Jiehao Li",
"Yingpeng Dai",
"Junzheng Wang",
"Xiaohang Su",
"Ruijun Ma",
"Jiehao Li",
"Yingpeng Dai",
"Junzheng Wang",
"Xiaohang Su",
"Ruijun Ma"
] | This article investigates the real-time semantic segmentation in robot engineering applications based on the Broad Learning System (BLS), and a novel Multi-level Enhancement Layers Network (MELNet) based on BLS framework is proposed for real-time vision tasks in a complex street scene on the unmanned mobile robot. This network mainly solves two problems: (1) mitigating the contradiction between ac... |
Vision-Based Large-scale 3D Semantic Mapping for Autonomous Driving Applications | https://ieeexplore.ieee.org/document/9811368/ | [
"Qing Cheng",
"Niclas Zeller",
"Daniel Cremers",
"Qing Cheng",
"Niclas Zeller",
"Daniel Cremers"
] | In this paper, we present a complete pipeline for 3D semantic mapping solely based on a stereo camera system. The pipeline comprises a direct sparse visual odometry frontend as well as a back-end for global optimization including GNSS integration, and semantic 3D point cloud labeling. We propose a simple but effective temporal voting scheme which improves the quality and consistency of the 3D poin... |
Prototype-Voxel Contrastive Learning for LiDAR Point Cloud Panoptic Segmentation | https://ieeexplore.ieee.org/document/9811638/ | [
"Minzhe Liu",
"Qiang Zhou",
"Hengshuang Zhao",
"Jianing Li",
"Yuan Du",
"Kurt Keutzer",
"Li Du",
"Shanghang Zhang",
"Minzhe Liu",
"Qiang Zhou",
"Hengshuang Zhao",
"Jianing Li",
"Yuan Du",
"Kurt Keutzer",
"Li Du",
"Shanghang Zhang"
] | LiDAR point cloud panoptic segmentation, including both semantic and instance segmentation, plays a critical role in meticulous scene understanding for autonomous driving. Existing 3D voxelized approaches either utilize 3D sparse convolution that only focuses on local scene understanding, or add extra and time-consuming PointNet branch to capture global feature structures. To address these limitat... |
Perception Engine Using a Multi-Sensor Head to Enable High-level Humanoid Robot Behaviors | https://ieeexplore.ieee.org/document/9812178/ | [
"Bhavyansh Mishra",
"Duncan Calvert",
"Brendon Ortolano",
"Max Asselmeier",
"Luke Fina",
"Stephen McCrory",
"Hakki Erhan Sevil",
"Robert Griffin",
"Bhavyansh Mishra",
"Duncan Calvert",
"Brendon Ortolano",
"Max Asselmeier",
"Luke Fina",
"Stephen McCrory",
"Hakki Erhan Sevil",
"Robert Griffin"
] | For achieving significant levels of autonomy, legged robot behaviors require perceptual awareness of both the terrain for traversal, as well as structures and objects in their surroundings for planning, obstacle avoidance, and high-level decision making. In this work, we present a perception engine for legged robots that extracts the necessary information for developing semantic, contextual, and m... |
Audio-Visual Grounding Referring Expression for Robotic Manipulation | https://ieeexplore.ieee.org/document/9811895/ | [
"Yefei Wang",
"Kaili Wang",
"Yi Wang",
"Di Guo",
"Huaping Liu",
"Fuchun Sun",
"Yefei Wang",
"Kaili Wang",
"Yi Wang",
"Di Guo",
"Huaping Liu",
"Fuchun Sun"
] | Referring expressions are commonly used when referring to a specific target in people's daily dialogue. In this paper, we develop a novel task of audio-visual grounding referring expression for robotic manipulation. The robot leverages both the audio and visual information to understand the referring expression in the given manipulation instruction and the corresponding manipulations are implement... |
TridentNetV2: Lightweight Graphical Global Plan Representations for Dynamic Trajectory Generation | https://ieeexplore.ieee.org/document/9811591/ | [
"David Paz",
"Hao Xiang",
"Andrew Liang",
"Henrik I. Christensen",
"David Paz",
"Hao Xiang",
"Andrew Liang",
"Henrik I. Christensen"
] | We present a framework for dynamic trajectory generation for autonomous navigation, which does not rely on HD maps as the underlying representation. High Definition (HD) maps have become a key component in most autonomous driving frameworks, which include complete road network information annotated at a centimeter-level that include traversable waypoints, lane information, and traffic signals. Ins... |
Hierarchical Representations and Explicit Memory: Learning Effective Navigation Policies on 3D Scene Graphs using Graph Neural Networks | https://ieeexplore.ieee.org/document/9812179/ | [
"Zachary Ravichandran",
"Lisa Peng",
"Nathan Hughes",
"J. Daniel Griffith",
"Luca Carlone",
"Zachary Ravichandran",
"Lisa Peng",
"Nathan Hughes",
"J. Daniel Griffith",
"Luca Carlone"
] | Representations are crucial for a robot to learn effective navigation policies. Recent work has shown that mid-level perceptual abstractions, such as depth estimates or 2D semantic segmentation, lead to more effective policies when provided as observations in place of raw sensor data (e.g., RGB images). However, such policies must still learn latent three-dimensional scene properties from mid-leve... |
Tactile Classification of Object Materials for Virtual Reality based Robot Teleoperation | https://ieeexplore.ieee.org/document/9811825/ | [
"Bukeikhan Omarali",
"Francesca Palermo",
"Kaspar Althoefer",
"Maurizio Valle",
"Ildar Farkhatdinov",
"Bukeikhan Omarali",
"Francesca Palermo",
"Kaspar Althoefer",
"Maurizio Valle",
"Ildar Farkhatdinov"
] | This work presents a method for tactile classification of materials for virtual reality (VR) based robot teleoperation. In our system, a human-operator uses a remotely controlled robot-manipulator with an optical fibre-based tactile and proximity sensor to scan surfaces of objects in a remote environment. Tactile and proximity data and the robot's end-effector state feedback are used for the class... |
Semi-Autonomous Teleoperation via Learning Non-Prehensile Manipulation Skills | https://ieeexplore.ieee.org/document/9811823/ | [
"Sangbeom Park",
"Yoonbyung Chai",
"Sunghyun Park",
"Jeongeun Park",
"Kyungjae Lee",
"Sungjoon Choi",
"Sangbeom Park",
"Yoonbyung Chai",
"Sunghyun Park",
"Jeongeun Park",
"Kyungjae Lee",
"Sungjoon Choi"
] | In this paper, we present a semi-autonomous teleoperation framework for a pick-and-place task using an RGB-D sensor. In particular, we assume that the target object is located in a cluttered environment where both prehensile grasping and non-prehensile manipulation are combined for efficient teleoperation. A trajectory-based reinforcement learning is utilized for learning the non-prehensile manipu... |
Towards 6DoF Bilateral Teleoperation of an Omnidirectional Aerial Vehicle for Aerial Physical Interaction | https://ieeexplore.ieee.org/document/9812346/ | [
"Mike Allenspach",
"Nicholas Lawrance",
"Marco Tognon",
"Roland Siegwart",
"Mike Allenspach",
"Nicholas Lawrance",
"Marco Tognon",
"Roland Siegwart"
] | Bilateral teleoperation offers an intriguing solution towards shared autonomy with aerial vehicles in contact-based inspection and manipulation tasks. Omnidirectional aerial robots allow for full pose operations, making them particularly attractive in such tasks. Naturally, the question arises whether standard bilateral teleoperation methodologies are suitable for use with these vehicles. In this ... |
Comparison of Haptic and Augmented Reality Visual Cues for Assisting Tele- manipulation | https://ieeexplore.ieee.org/document/9811669/ | [
"Tsung-Chi Lin",
"Achyuthan Unni Krishnan",
"Zhi Li",
"Tsung-Chi Lin",
"Achyuthan Unni Krishnan",
"Zhi Li"
] | Robot teleoperation via human motion tracking has been proven to be easy to learn, intuitive to operate, and facilitate faster task execution than existing baselines. However, precise control while performing the dexterous telemanipulation tasks is still a challenge. In this paper, we implement sensory augmentation in terms of haptic and augmented reality visual cues to represent four types of inf... |
Immersive Virtual Walking System Using an Avatar Robot | https://ieeexplore.ieee.org/document/9811588/ | [
"Kengkij Promsutipong",
"Jose V. Salazar Luces",
"Ankit A. Ravankar",
"Seyed Amir Tafrishi",
"Yasuhisa Hirata",
"Kengkij Promsutipong",
"Jose V. Salazar Luces",
"Ankit A. Ravankar",
"Seyed Amir Tafrishi",
"Yasuhisa Hirata"
] | The ongoing COVID-19 pandemic has enforced governments across the world to impose social restrictions on the movement of people and confined them to their homes to avoid the spread of the disease. This not only forbids them from leaving their homes but also greatly reduces their physical activities. This situation has brought attention to virtual technologies such as virtual tours or telepresence ... |
Blending Primitive Policies in Shared Control for Assisted Teleoperation | https://ieeexplore.ieee.org/document/9812414/ | [
"Guilherme Maeda",
"Guilherme Maeda"
] | Movement primitives have the property to accom-modate changes in the robot state while maintaining attraction to the original policy. As such, we investigate the use of primitives as a blending mechanism by considering that state deviations from the original policy are caused by user inputs. As the primitive recovers from the user input, it implicitly blends human and robot policies without requir... |
Maximal Manipulation Framework using Quadratic Programming for a Teleoperated Robotic System with Articulated bodies | https://ieeexplore.ieee.org/document/9811602/ | [
"Donghyeon Lee",
"Dongwoo Ko",
"Wan Kyun Chung",
"Keehoon Kim",
"Donghyeon Lee",
"Dongwoo Ko",
"Wan Kyun Chung",
"Keehoon Kim"
] | This paper proposes a teleoperation framework to exploit the maximum manipulation capability during teleoperation. Here, exploiting maximum manipulation capacity means that the robot moves with its maximum control input while not violating the given constraints, and it is a nonlinear optimization problem with nonlinear constraints which is hard to be solved. The proposed framework relaxes the opti... |
Augmenting Imitation Experience via Equivariant Representations | https://ieeexplore.ieee.org/document/9811885/ | [
"Dhruv Sharma",
"Alihusein Kuwajerwala",
"Florian Shkurti",
"Dhruv Sharma",
"Alihusein Kuwajerwala",
"Florian Shkurti"
] | The robustness of visual navigation policies trained through imitation often hinges on the augmentation of the training image-action pairs. Traditionally, this has been done by collecting data from multiple cameras, by using standard data augmentations from computer vision, such as adding random noise to each image, or by synthesizing training images. In this paper we show that there is another pr... |
Depth-Aware Vision-and-Language Navigation using Scene Query Attention Network | https://ieeexplore.ieee.org/document/9811921/ | [
"Sinan Tan",
"Mengmeng Ge",
"Di Guo",
"Huaping Liu",
"Fuchun Sun",
"Sinan Tan",
"Mengmeng Ge",
"Di Guo",
"Huaping Liu",
"Fuchun Sun"
] | Vision-and-language navigation (VLN) has been an important task in the field of Robotics and Computer Vision. However, most existing vision-and-language navigation models only use features extracted from RGB observation as input, while robots can utilize depth sensors in the real world. Existing research has also shown that simply adding a depth stream to neural models could only provide a margina... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.