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GraNet: A Multi-Level Graph Network for 6-DoF Grasp Pose Generation in Cluttered Scenes | https://ieeexplore.ieee.org/document/10341549/ | [
"Haowen Wang",
"Wanhao Niu",
"Chungang Zhuang",
"Haowen Wang",
"Wanhao Niu",
"Chungang Zhuang"
] | 6-DoF object-agnostic grasping in unstructured environments is a critical yet challenging task in robotics. Most current works use non-optimized approaches to sample grasp locations and learn spatial features without concerning the grasping task. This paper proposes GraNet, a graph-based grasp pose generation framework that translates a point cloud scene into multi-level graphs and propagates feat... |
Modular Neural Network Policies for Learning In-Flight Object Catching with a Robot Hand-Arm System | https://ieeexplore.ieee.org/document/10341463/ | [
"Wenbin Hu",
"Fernando Acero",
"Eleftherios Triantafyllidis",
"Zhaocheng Liu",
"Zhibin Li",
"Wenbin Hu",
"Fernando Acero",
"Eleftherios Triantafyllidis",
"Zhaocheng Liu",
"Zhibin Li"
] | We present a modular framework designed to enable a robot hand-arm system to learn how to catch flying objects, a task that requires fast, reactive, and accurately-timed robot motions. Our framework consists of five core modules: (i) an object state estimator that learns object trajectory prediction, (ii) a catching pose quality network that learns to score and rank object poses for catching, (iii... |
GVCCI: Lifelong Learning of Visual Grounding for Language-Guided Robotic Manipulation | https://ieeexplore.ieee.org/document/10342021/ | [
"Junghyun Kim",
"Gi-Cheon Kang",
"Jaein Kim",
"Suyeon Shin",
"Byoung-Tak Zhang",
"Junghyun Kim",
"Gi-Cheon Kang",
"Jaein Kim",
"Suyeon Shin",
"Byoung-Tak Zhang"
] | Language-Guided Robotic Manipulation (LGRM) is a challenging task as it requires a robot to understand human instructions to manipulate everyday objects. Recent approaches in LGRM rely on pre-trained Visual Grounding (VG) models to detect objects without adapting to manipulation environments. This results in a performance drop due to a substantial domain gap between the pre-training and real-world... |
Bag All You Need: Learning a Generalizable Bagging Strategy for Heterogeneous Objects | https://ieeexplore.ieee.org/document/10341841/ | [
"Arpit Bahety",
"Shreeya Jain",
"Huy Ha",
"Nathalie Hager",
"Benjamin Burchfiel",
"Eric Cousineau",
"Siyuan Feng",
"Shuran Song",
"Arpit Bahety",
"Shreeya Jain",
"Huy Ha",
"Nathalie Hager",
"Benjamin Burchfiel",
"Eric Cousineau",
"Siyuan Feng",
"Shuran Song"
] | We introduce a practical robotics solution for the task of heterogeneous bagging, requiring the placement of multiple rigid and deformable objects into a deformable bag. This is a difficult task as it features complex interactions between multiple highly deformable objects under limited observability. To tackle these challenges, we propose a robotic system consisting of two learned policies: a rea... |
Multi-Source Fusion for Voxel-Based 7-DoF Grasping Pose Estimation | https://ieeexplore.ieee.org/document/10341840/ | [
"Junning Qiu",
"Fei Wang",
"Zheng Dang",
"Junning Qiu",
"Fei Wang",
"Zheng Dang"
] | In this work, we tackle the problem of 7-DoF grasping pose estimation(6-DoF with the opening width of parallel-jaw gripper) from point cloud data, which is a fundamental task in robotic manipulation. Most existing methods adopt 3D voxel CNNs as the backbone for their efficiency in handling unordered point cloud data. However, we found that these approaches overlook detailed information of the poin... |
VL-Grasp: a 6-Dof Interactive Grasp Policy for Language-Oriented Objects in Cluttered Indoor Scenes | https://ieeexplore.ieee.org/document/10341379/ | [
"Yuhao Lu",
"Yixuan Fan",
"Beixing Deng",
"Fangfu Liu",
"Yali Li",
"Shengjin Wang",
"Yuhao Lu",
"Yixuan Fan",
"Beixing Deng",
"Fangfu Liu",
"Yali Li",
"Shengjin Wang"
] | Robotic grasping faces new challenges in human-robot-interaction scenarios. We consider the task that the robot grasps a target object designated by human's language directives. The robot not only needs to locate a target based on vision-and-language information, but also needs to predict the reasonable grasp pose candidate at various views and postures. In this work, we propose a novel interactiv... |
QDP: Learning to Sequentially Optimise Quasi-Static and Dynamic Manipulation Primitives for Robotic Cloth Manipulation | https://ieeexplore.ieee.org/document/10342002/ | [
"David Blanco-Mulero",
"Gokhan Alcan",
"Fares J. Abu-Dakka",
"Ville Kyrki",
"David Blanco-Mulero",
"Gokhan Alcan",
"Fares J. Abu-Dakka",
"Ville Kyrki"
] | Pre-defined manipulation primitives are widely used for cloth manipulation. However, cloth properties such as its stiffness or density can highly impact the performance of these primitives. Although existing solutions have tackled the parameterisation of pick and place locations, the effect of factors such as the velocity or trajectory of quasi-static and dynamic manipulation primitives has been n... |
Robust Visual Sim-to-Real Transfer for Robotic Manipulation | https://ieeexplore.ieee.org/document/10342471/ | [
"Ricardo Garcia",
"Robin Strudel",
"Shizhe Chen",
"Etienne Arlaud",
"Ivan Laptev",
"Cordelia Schmid",
"Ricardo Garcia",
"Robin Strudel",
"Shizhe Chen",
"Etienne Arlaud",
"Ivan Laptev",
"Cordelia Schmid"
] | Learning visuomotor policies in simulation is much safer and cheaper than in the real world. However, due to discrepancies between the simulated and real data, simulator-trained policies often fail when transferred to real robots. One common approach to bridge the visual sim-to-real domain gap is domain randomization (DR). While previous work mainly evaluates DR for disembodied tasks, such as pose... |
Multi-Dimensional Deformable Object Manipulation Using Equivariant Models | https://ieeexplore.ieee.org/document/10341618/ | [
"Tianyu Fu",
"Yang Tang",
"Tianyu Wu",
"Xiaowu Xia",
"Jianrui Wang",
"Chaoqiang Zhao",
"Tianyu Fu",
"Yang Tang",
"Tianyu Wu",
"Xiaowu Xia",
"Jianrui Wang",
"Chaoqiang Zhao"
] | Manipulating deformable objects, such as ropes (1D), fabrics (2D), and bags (3D), poses a significant challenge in robotics research due to their high degree of freedom in physical state and nonlinear dynamics. Compared with single-dimensional deformable objects, multi-dimensional object manipulation suffers from the difficulty in recognizing the characteristics of the object correctly and making ... |
Adversarial Object Rearrangement in Constrained Environments with Heterogeneous Graph Neural Networks | https://ieeexplore.ieee.org/document/10342412/ | [
"Xibai Lou",
"Houjian Yu",
"Ross Worobel",
"Yang Yang",
"Changhyun Choi",
"Xibai Lou",
"Houjian Yu",
"Ross Worobel",
"Yang Yang",
"Changhyun Choi"
] | Adversarial object rearrangement in the real world (e.g., previously unseen or oversized items in kitchens and stores) could benefit from understanding task scenes, which inherently entail heterogeneous components such as current objects, goal objects, and environmental constraints. The semantic relationships among these components are distinct from each other and crucial for multi-skilled robots ... |
Probabilistic Slide-support Manipulation Planning in Clutter | https://ieeexplore.ieee.org/document/10342030/ | [
"Shusei Nagato",
"Tomohiro Motoda",
"Takao Nishi",
"Petit Damien",
"Takuya Kiyokawa",
"Weiwei Wan",
"Kensuke Harada",
"Shusei Nagato",
"Tomohiro Motoda",
"Takao Nishi",
"Petit Damien",
"Takuya Kiyokawa",
"Weiwei Wan",
"Kensuke Harada"
] | To safely and efficiently extract an object from the clutter, this paper presents a bimanual manipulation planner in which one hand of the robot is used to slide the target object out of the clutter while the other hand is used to support the surrounding objects to prevent the clutter from collapsing. Our method uses a neural network to predict the physical phenomena of the clutter when the target... |
GOATS: Goal Sampling Adaptation for Scooping with Curriculum Reinforcement Learning | https://ieeexplore.ieee.org/document/10342221/ | [
"Yaru Niu",
"Shiyu Jin",
"Zeqing Zhang",
"Jiacheng Zhu",
"Ding Zhao",
"Liangjun Zhang",
"Yaru Niu",
"Shiyu Jin",
"Zeqing Zhang",
"Jiacheng Zhu",
"Ding Zhao",
"Liangjun Zhang"
] | In this work, we first formulate the problem of robotic water scooping using goal-conditioned reinforcement learning. This task is particularly challenging due to the complex dynamics of fluid and the need to achieve multi-modal goals. The policy is required to successfully reach both position goals and water amount goals, which leads to a large convoluted goal state space. To overcome these chall... |
Tight Collision Probability for UAV Motion Planning in Uncertain Environment | https://ieeexplore.ieee.org/document/10342141/ | [
"Tianyu Liu",
"Fu Zhang",
"Fei Gao",
"Jia Pan",
"Tianyu Liu",
"Fu Zhang",
"Fei Gao",
"Jia Pan"
] | Operating unmanned aerial vehicles (UAVs) in complex environments that feature dynamic obstacles and external disturbances poses significant challenges, primarily due to the inherent uncertainty in such scenarios. Additionally, inaccurate robot localization and modeling errors further exacerbate these challenges. Recent research on UAV motion planning in static environments has been unable to cope... |
Dodging Like A Bird: An Inverted Dive Maneuver Taking by Lifting-Wing Multicopters | https://ieeexplore.ieee.org/document/10341551/ | [
"Wenhan Gao",
"Shuai Wang",
"Quan Quan",
"Wenhan Gao",
"Shuai Wang",
"Quan Quan"
] | It is crucial for hybrid unmanned aerial vehicles, such as lifting-wing multicopters, to plan a continuous, smooth, and collision-free trajectory to avoid obstacles. Unlike quad-copters, which typically work in indoor environments, lifting-wing multicopters typically fly at a high altitude with a high cruising speed, requiring higher maneuverability in the vertical direction. Inspired by birds, li... |
Model-Based Planning and Control for Terrestrial-Aerial Bimodal Vehicles with Passive Wheels | https://ieeexplore.ieee.org/document/10342188/ | [
"Ruibin Zhang",
"Junxiao Lin",
"Yuze Wu",
"Yuman Gao",
"Chi Wang",
"Chao Xu",
"Yanjun Cao",
"Fei Gao",
"Ruibin Zhang",
"Junxiao Lin",
"Yuze Wu",
"Yuman Gao",
"Chi Wang",
"Chao Xu",
"Yanjun Cao",
"Fei Gao"
] | Terrestrial and aerial bimodal vehicles have gained widespread attention due to their cross-domain maneuverability. Nevertheless, their bimodal dynamics significantly increase the complexity of motion planning and control, thus hindering robust and efficient autonomous navigation in unknown environments. To resolve this issue, we develop a model-based planning and control framework for terrestrial... |
Polynomial-Based Online Planning for Autonomous Drone Racing in Dynamic Environments | https://ieeexplore.ieee.org/document/10342456/ | [
"Qianhao Wang",
"Dong Wang",
"Chao Xu",
"Alan Gao",
"Fei Gao",
"Qianhao Wang",
"Dong Wang",
"Chao Xu",
"Alan Gao",
"Fei Gao"
] | In recent years, there is a noteworthy advance-ment in autonomous drone racing. However, the primary focus is on attaining execution times, while scant attention is given to the challenges of dynamic environments. The high-speed nature of racing scenarios, coupled with the potential for unforeseeable environmental alterations, present stringent requirements for online replanning and its timeliness... |
Autonomous Power Line Inspection with Drones via Perception-Aware MPC | https://ieeexplore.ieee.org/document/10341871/ | [
"Jiaxu Xing",
"Giovanni Cioffi",
"Javier Hidalgo-Carrió",
"Davide Scaramuzza",
"Jiaxu Xing",
"Giovanni Cioffi",
"Javier Hidalgo-Carrió",
"Davide Scaramuzza"
] | Drones have the potential to revolutionize power line inspection by increasing productivity, reducing inspection time, improving data quality, and eliminating the risks for human operators. Current state-of-the-art systems for power line inspection have two shortcomings: (i) control is decoupled from perception and needs accurate information about the location of the power lines and masts; (ii) ob... |
A Perching and Tilting Aerial Robot for Precise and Versatile Power Tool Work on Vertical Walls | https://ieeexplore.ieee.org/document/10342274/ | [
"Roman Dautzenberg",
"Timo Küster",
"Timon Mathis",
"Yann Roth",
"Curdin Steinauer",
"Gabriel Käppeli",
"Julian Santen",
"Alina Arranhado",
"Friederike Biffar",
"Till Kötter",
"Christian Lanegger",
"Mike Allenspach",
"Roland Siegwart",
"Rik Bähnemann",
"Roman Dautzenberg",
"Timo Küster",
"Timon Mathis",
"Yann Roth",
"Curdin Steinauer",
"Gabriel Käppeli",
"Julian Santen",
"Alina Arranhado",
"Friederike Biffar",
"Till Kötter",
"Christian Lanegger",
"Mike Allenspach",
"Roland Siegwart",
"Rik Bähnemann"
] | Drilling, grinding, and setting anchors on vertical walls are fundamental processes in everyday construction work. Manually doing these works is error-prone, potentially dangerous, and elaborate at height. Today, heavy mobile ground robots can perform automatic power tool work. However, aerial vehicles could be deployed in untraversable environments and reach inaccessible places. Existing drone de... |
Resource-Constrained Station-Keeping for Latex Balloons Using Reinforcement Learning | https://ieeexplore.ieee.org/document/10341711/ | [
"Jack Saunders",
"Loïc Prenevost",
"Özgür Şimşek",
"Alan Hunter",
"Wenbin Li",
"Jack Saunders",
"Loïc Prenevost",
"Özgür Şimşek",
"Alan Hunter",
"Wenbin Li"
] | High altitude balloons have proved useful for ecological aerial surveys, atmospheric monitoring, and communication relays. However, due to weight and power constraints, there is a need to investigate alternate modes of propulsion to navigate in the stratosphere. Very recently, reinforcement learning has been proposed as a control scheme to maintain balloons in the region of a fixed location, facil... |
A Light-Weight, Low-Cost, and Sustainable Planning System for UAVs Using a Local Map Origin Update Approach | https://ieeexplore.ieee.org/document/10342455/ | [
"Dasol Lee",
"Jinche La",
"Sanghyun Joo",
"Dasol Lee",
"Jinche La",
"Sanghyun Joo"
] | This paper proposes a sustainable planning system for small-sized unmanned aerial vehicles (UAVs). Our mapping module of the system uses a voxel array as data structure with an introduced feature which is local map origin update. This approach has clear advantages that the planning system can sustainably plan trajectories regardless of operating radius and flight distance, and it shows fastest inv... |
Bubble Explorer: Fast UAV Exploration in Large-Scale and Cluttered 3D-Environments Using Occlusion-Free Spheres | https://ieeexplore.ieee.org/document/10342348/ | [
"Benxu Tang",
"Yunfan Ren",
"Fangcheng Zhu",
"Rui He",
"Siqi Liang",
"Fanze Kong",
"Fu Zhang",
"Benxu Tang",
"Yunfan Ren",
"Fangcheng Zhu",
"Rui He",
"Siqi Liang",
"Fanze Kong",
"Fu Zhang"
] | Autonomous exploration is a crucial aspect of robotics that has numerous applications. Most of the existing methods greedily choose goals that maximize immediate reward. This strategy is computationally efficient but insufficient for overall exploration efficiency. In recent years, some state-of-the-art methods are proposed, which generate a global coverage path and significantly improve overall e... |
UPPLIED: UAV Path Planning for Inspection Through Demonstration | https://ieeexplore.ieee.org/document/10342478/ | [
"Shyam Sundar Kannan",
"Vishnunandan L. N. Venkatesh",
"Revanth Krishna Senthilkumaran",
"Byung-Cheol Min",
"Shyam Sundar Kannan",
"Vishnunandan L. N. Venkatesh",
"Revanth Krishna Senthilkumaran",
"Byung-Cheol Min"
] | In this paper, a new demonstration-based path-planning framework for the visual inspection of large structures using UAVs is proposed. We introduce UPPLIED: UAV Path PLanning for InspEction through Demonstration, which utilizes a demonstrated trajectory to generate a new trajectory to inspect other structures of the same kind. The demonstrated trajectory can inspect specific regions of the structu... |
Self-Supervised Instance Segmentation by Grasping | https://ieeexplore.ieee.org/document/10342432/ | [
"YuXuan Liu",
"Xi Chen",
"Pieter Abbeel",
"YuXuan Liu",
"Xi Chen",
"Pieter Abbeel"
] | Instance segmentation is a fundamental skill for many robotic applications. We propose a self-supervised method that uses grasp interactions to collect segmentation supervision for an instance segmentation model. When a robot grasps an item, the mask of that grasped item can be inferred from the images of the scene before and after the grasp. Leveraging this insight, we learn a grasp segmentation ... |
Fusing Visual Appearance and Geometry for Multi-Modality 6DoF Object Tracking | https://ieeexplore.ieee.org/document/10341961/ | [
"Manuel Stoiber",
"Mariam Elsayed",
"Anne E. Reichert",
"Florian Steidle",
"Dongheui Lee",
"Rudolph Triebel",
"Manuel Stoiber",
"Mariam Elsayed",
"Anne E. Reichert",
"Florian Steidle",
"Dongheui Lee",
"Rudolph Triebel"
] | In many applications of advanced robotic manipulation, six degrees of freedom (6DoF) object pose estimates are continuously required. In this work, we develop a multi-modality tracker that fuses information from visual appearance and geometry to estimate object poses. The algorithm extends our previous method ICG, which uses geometry, to additionally consider surface appearance. In general, object... |
Viewpoint Push Planning for Mapping of Unknown Confined Spaces | https://ieeexplore.ieee.org/document/10341809/ | [
"Nils Dengler",
"Sicong Pan",
"Vamsi Kalagaturu",
"Rohit Menon",
"Murad Dawood",
"Maren Bennewitz",
"Nils Dengler",
"Sicong Pan",
"Vamsi Kalagaturu",
"Rohit Menon",
"Murad Dawood",
"Maren Bennewitz"
] | Viewpoint planning is an important task in any application where objects or scenes need to be viewed from different angles to achieve sufficient coverage. The mapping of confined spaces such as shelves is an especially challenging task since objects occlude each other and the scene can only be observed from the front, posing limitations on the possible viewpoints. In this paper, we propose a deep ... |
Depth-Based 6DoF Object Pose Estimation Using Swin Transformer | https://ieeexplore.ieee.org/document/10342215/ | [
"Zhujun Li",
"Ioannis Stamos",
"Zhujun Li",
"Ioannis Stamos"
] | Accurately estimating the 6D pose of objects is crucial for many applications, such as robotic grasping, autonomous driving, and augmented reality. However, this task becomes more challenging in poor lighting conditions or when dealing with textureless objects. To address this issue, depth images are becoming an increasingly popular choice due to their invariance to a scene's appearance and the im... |
DR-Pose: A Two-Stage Deformation-and-Registration Pipeline for Category-Level 6D Object Pose Estimation | https://ieeexplore.ieee.org/document/10341552/ | [
"Lei Zhou",
"Zhiyang Liu",
"Runze Gan",
"Haozhe Wang",
"Marcelo H. Ang",
"Lei Zhou",
"Zhiyang Liu",
"Runze Gan",
"Haozhe Wang",
"Marcelo H. Ang"
] | Category-level object pose estimation involves estimating the 6D pose and the 3D metric size of objects from predetermined categories. While recent approaches take categorical shape prior information as reference to improve pose estimation accuracy, the single-stage network design and training manner lead to sub-optimal performance since there are two distinct tasks in the pipeline. In this paper,... |
Learning from Pixels with Expert Observations | https://ieeexplore.ieee.org/document/10342043/ | [
"Minh-Huy Hoang",
"Long Dinh",
"Hai Nguyen",
"Minh-Huy Hoang",
"Long Dinh",
"Hai Nguyen"
] | In reinforcement learning (RL), sparse rewards can present a significant challenge. Fortunately, expert actions can be utilized to overcome this issue. However, acquiring explicit expert actions can be costly, and expert observations are often more readily available. This paper presents a new approach that uses expert observations for learning in robot manipulation tasks with sparse rewards from p... |
RMBench: Benchmarking Deep Reinforcement Learning for Robotic Manipulator Control | https://ieeexplore.ieee.org/document/10342479/ | [
"Yanfei Xiang",
"Xin Wang",
"Shu Hu",
"Bin Zhu",
"Xiaomeng Huang",
"Xi Wu",
"Siwei Lyu",
"Yanfei Xiang",
"Xin Wang",
"Shu Hu",
"Bin Zhu",
"Xiaomeng Huang",
"Xi Wu",
"Siwei Lyu"
] | Reinforcement learning is used to tackle complex tasks with high-dimensional sensory inputs. Over the past decade, a wide range of reinforcement learning algorithms have been developed, with recent progress benefiting from deep learning for raw sensory signal representation. This raises a natural question: how well do these algorithms perform across different robotic manipulation tasks? To objecti... |
Shape Completion with Prediction of Uncertain Regions | https://ieeexplore.ieee.org/document/10342487/ | [
"Matthias Humt",
"Dominik Winkelbauer",
"Ulrich Hillenbrand",
"Matthias Humt",
"Dominik Winkelbauer",
"Ulrich Hillenbrand"
] | Shape completion, i.e., predicting the complete geometry of an object from a partial observation, is highly relevant for several downstream tasks, most notably robotic manipulation. When basing planning or prediction of real grasps on object shape reconstruction, an indication of severe geometric uncertainty is indispensable. In particular, there can be an irreducible uncertainty in extended regio... |
Structure from Action: Learning Interactions for 3D Articulated Object Structure Discovery | https://ieeexplore.ieee.org/document/10342135/ | [
"Neil Nie",
"Samir Yitzhak Gadre",
"Kiana Ehsani",
"Shuran Song",
"Neil Nie",
"Samir Yitzhak Gadre",
"Kiana Ehsani",
"Shuran Song"
] | We introduce Structure from Action (SfA), a framework to discover 3D part geometry and joint parameters of unseen articulated objects via a sequence of inferred interactions. Our key insight is that 3D interaction and perception should be considered in conjunction to construct 3D articulated CAD models, especially for categories not seen during training. By selecting informative interactions, Sf A... |
Object-Oriented Option Framework for Robotics Manipulation in Clutter | https://ieeexplore.ieee.org/document/10342335/ | [
"Jing-Cheng Pang",
"Si-Hang Yang",
"Xiong-Hui Chen",
"Xinyu Yang",
"Yang Yu",
"Mas Ma",
"Ziqi Guo",
"Howard Yang",
"Bill Huang",
"Jing-Cheng Pang",
"Si-Hang Yang",
"Xiong-Hui Chen",
"Xinyu Yang",
"Yang Yu",
"Mas Ma",
"Ziqi Guo",
"Howard Yang",
"Bill Huang"
] | Domestic service robots are becoming increasingly popular due to their ability to help people with household tasks. These robots often encounter the challenge of manipulating objects in cluttered environments (MoC), which is difficult due to the complexity of effective planning and control. Previous solutions involved designing specific action primitives and planning paradigms. However, the pre-co... |
Weakly Supervised Referring Expression Grounding via Dynamic Self-Knowledge Distillation | https://ieeexplore.ieee.org/document/10341909/ | [
"Jinpeng Mi",
"Zhiqian Chen",
"Jianwei Zhang",
"Jinpeng Mi",
"Zhiqian Chen",
"Jianwei Zhang"
] | Weakly supervised referring expression grounding (WREG) is an attractive and challenging task for grounding target regions in images by understanding given referring expressions. WREG learns to ground target objects without the manual annotations between image regions and referring expressions during the model training phase. Different from the predominant grounding pattern of existing models, whi... |
EventTransAct: A Video Transformer-Based Framework for Event-Camera Based Action Recognition | https://ieeexplore.ieee.org/document/10341740/ | [
"Tristan de Blegiers",
"Ishan Rajendrakumar Dave",
"Adeel Yousaf",
"Mubarak Shah",
"Tristan de Blegiers",
"Ishan Rajendrakumar Dave",
"Adeel Yousaf",
"Mubarak Shah"
] | Recognizing and comprehending human actions and gestures is a crucial perception requirement for robots to interact with humans and carry out tasks in diverse domains, including service robotics, healthcare, and manufacturing. Event cameras, with their ability to capture fast-moving objects at a high temporal resolution, offer new opportunities compared to standard action recognition in RGB videos... |
Virtual Ski Training System that Allows Beginners to Acquire Ski Skills Based on Physical and Visual Feedbacks | https://ieeexplore.ieee.org/document/10342020/ | [
"Yushi Okada",
"Chanjin Seo",
"Shunichi Miyakawa",
"Motofumi Taniguchi",
"Kazuyuki Kanosue",
"Hiroyuki Ogata",
"Jun Ohya",
"Yushi Okada",
"Chanjin Seo",
"Shunichi Miyakawa",
"Motofumi Taniguchi",
"Kazuyuki Kanosue",
"Hiroyuki Ogata",
"Jun Ohya"
] | This paper proposes a ski training system using VR (Virtual Reality) that enables beginners to acquire skiing skills without going to an actual ski ground. The proposed system obtains the speed of skiing based on the center of pressure (COP) of each player's foot. The first-person perspective of skiing at the obtained speed down a ski slope is fed back to the player as a VR image. Experiments were... |
Attention-Based VR Facial Animation with Visual Mouth Camera Guidance for Immersive Telepresence Avatars | https://ieeexplore.ieee.org/document/10342522/ | [
"Andre Rochow",
"Max Schwarz",
"Sven Behnke",
"Andre Rochow",
"Max Schwarz",
"Sven Behnke"
] | Facial animation in virtual reality environments is essential for applications that necessitate clear visibility of the user's face and the ability to convey emotional signals. In our scenario, we animate the face of an operator who controls a robotic Avatar system. The use of facial animation is particularly valuable when the perception of interacting with a specific individual, rather than just ... |
Test-Time Adaptation for Point Cloud Upsampling Using Meta-Learning | https://ieeexplore.ieee.org/document/10341345/ | [
"Ahmed Hatem",
"Yiming Qian",
"Yang Wang",
"Ahmed Hatem",
"Yiming Qian",
"Yang Wang"
] | Affordable 3D scanners often produce sparse and non-uniform point clouds that negatively impact downstream applications in robotic systems. While existing point cloud upsampling architectures have demonstrated promising results on standard benchmarks, they tend to experience significant performance drops when the test data have different distributions from the training data. To address this issue,... |
Revisiting Event-Based Video Frame Interpolation | https://ieeexplore.ieee.org/document/10341804/ | [
"Jiaben Chen",
"Yichen Zhu",
"Dongze Lian",
"Jiaqi Yang",
"Yifu Wang",
"Renrui Zhang",
"Xinhang Liu",
"Shenhan Qian",
"Laurent Kneip",
"Shenghua Gao",
"Jiaben Chen",
"Yichen Zhu",
"Dongze Lian",
"Jiaqi Yang",
"Yifu Wang",
"Renrui Zhang",
"Xinhang Liu",
"Shenhan Qian",
"Laurent Kneip",
"Shenghua Gao"
] | Dynamic vision sensors or event cameras provide rich complementary information for video frame interpolation. Existing state-of-the-art methods follow the paradigm of combining both synthesis-based and warping networks. However, few of those methods fully respect the intrinsic characteristics of events streams. Given that event cameras only encode intensity changes and polarity rather than color i... |
Revisiting Deformable Convolution for Depth Completion | https://ieeexplore.ieee.org/document/10342026/ | [
"Xinglong Sun",
"Jean Ponce",
"Yu-Xiong Wang",
"Xinglong Sun",
"Jean Ponce",
"Yu-Xiong Wang"
] | Depth completion, which aims to generate high-quality dense depth maps from sparse depth maps, has attracted increasing attention in recent years. Previous work usually employs RGB images as guidance, and introduces iterative spatial propagation to refine estimated coarse depth maps. However, most of the propagation refinement methods require several iterations and suffer from a fixed receptive fi... |
Long-Distance Gesture Recognition Using Dynamic Neural Networks | https://ieeexplore.ieee.org/document/10342147/ | [
"Shubhang Bhatnagar",
"Sharath Gopal",
"Narendra Ahuja",
"Liu Ren",
"Shubhang Bhatnagar",
"Sharath Gopal",
"Narendra Ahuja",
"Liu Ren"
] | Gestures form an important medium of communication between humans and machines. An overwhelming majority of existing gesture recognition methods are tailored to a scenario where humans and machines are located very close to each other. This short-distance assumption does not hold true for several types of interactions, for example gesture-based interactions with a floor cleaning robot or with a dr... |
Neural Implicit Vision-Language Feature Fields | https://ieeexplore.ieee.org/document/10342275/ | [
"Kenneth Blomqvist",
"Francesco Milano",
"Jen Jen Chung",
"Lionel Ott",
"Roland Siegwart",
"Kenneth Blomqvist",
"Francesco Milano",
"Jen Jen Chung",
"Lionel Ott",
"Roland Siegwart"
] | Recently, groundbreaking results have been presented on open-vocabulary semantic image segmentation. Such methods segment each pixel in an image into arbitrary categories provided at run-time in the form of text prompts, as opposed to a fixed set of classes defined at training time. In this work, we present a zero-shot volumetric open-vocabulary semantic scene segmentation method. Our method build... |
Language Guided Robotic Grasping with Fine-Grained Instructions | https://ieeexplore.ieee.org/document/10342331/ | [
"Qiang Sun",
"Haitao Lin",
"Ying Fu",
"Yanwei Fu",
"Xiangyang Xue",
"Qiang Sun",
"Haitao Lin",
"Ying Fu",
"Yanwei Fu",
"Xiangyang Xue"
] | Given a single RGB image and the attribute-rich language instructions, this paper investigates the novel problem of using Fine-grained instructions for the Language guided robotic Grasping (FLarG). This problem is made challenging by learning fine-grained language descriptions to ground target objects. Recent advances have been made in visually grounding the objects simply by several coarse attrib... |
Whole Shape Estimation of Transparent Object from Its Contour using Statistical Shape Model | https://ieeexplore.ieee.org/document/10342400/ | [
"Kaihei Okada",
"Riku Kobayashi",
"Tokuo Tsuji",
"Tatsuhiro Hiramitsu",
"Hiroaki Seki",
"Toshihiro Nishimura",
"Yosuke Suzuki",
"Tetsuyou Watanabe",
"Kaihei Okada",
"Riku Kobayashi",
"Tokuo Tsuji",
"Tatsuhiro Hiramitsu",
"Hiroaki Seki",
"Toshihiro Nishimura",
"Yosuke Suzuki",
"Tetsuyou Watanabe"
] | This study presents a method for estimating the three-dimensional (3D) shapes of transparent objects from an RGB-D image using a statistical shape model. Statistical shape models compress the dimensions of multiple shapes to represent shape variations using fewer parameters. It is difficult to measure the depth of a transparent object using sensors. Therefore, the statistical shape model is deform... |
Off the Radar: Uncertainty-Aware Radar Place Recognition with Introspective Querying and Map Maintenance | https://ieeexplore.ieee.org/document/10341965/ | [
"Jianhao Yuan",
"Paul Newman",
"Matthew Gadd",
"Jianhao Yuan",
"Paul Newman",
"Matthew Gadd"
] | Localisation with Frequency-Modulated Continuous-Wave (FMCW) radar has gained increasing interest due to its inherent resistance to challenging environments. However, complex artefacts of the radar measurement process require appropriate uncertainty estimation - to ensure the safe and reliable application of this promising sensor modality. In this work, we propose a multi-session map management sy... |
Global Localization in Unstructured Environments Using Semantic Object Maps Built from Various Viewpoints | https://ieeexplore.ieee.org/document/10342267/ | [
"Jacqueline Ankenbauer",
"Parker C. Lusk",
"Annika Thomas",
"Jonathan P. How",
"Jacqueline Ankenbauer",
"Parker C. Lusk",
"Annika Thomas",
"Jonathan P. How"
] | We present a novel framework for global localization and guided relocalization of a vehicle in an unstructured environment. Compared to existing methods, our pipeline does not rely on cues from urban fixtures (e.g., lane markings, buildings), nor does it make assumptions that require the vehicle to be navigating on a road network. Instead, we achieve localization in both urban and non-urban enviro... |
Constructing Metric-Semantic Maps Using Floor Plan Priors for Long-Term Indoor Localization | https://ieeexplore.ieee.org/document/10341595/ | [
"Nicky Zimmerman",
"Matteo Sodano",
"Elias Marks",
"Jens Behley",
"Cyrill Stachniss",
"Nicky Zimmerman",
"Matteo Sodano",
"Elias Marks",
"Jens Behley",
"Cyrill Stachniss"
] | Object-based maps are relevant for scene under-standing since they integrate geometric and semantic information of the environment, allowing autonomous robots to robustly localize and interact with on objects. In this paper, we address the task of constructing a metric-semantic map for the purpose of long-term object-based localization. We exploit 3D object detections from monocular RGB frames for... |
DisPlacing Objects: Improving Dynamic Vehicle Detection via Visual Place Recognition under Adverse Conditions | https://ieeexplore.ieee.org/document/10341550/ | [
"Stephen Hausler",
"Sourav Garg",
"Punarjay Chakravarty",
"Shubham Shrivastava",
"Ankit Vora",
"Michael Milford",
"Stephen Hausler",
"Sourav Garg",
"Punarjay Chakravarty",
"Shubham Shrivastava",
"Ankit Vora",
"Michael Milford"
] | Can knowing where you are assist in perceiving objects in your surroundings, especially under adverse weather and lighting conditions? In this work we investigate whether a prior map can be leveraged to aid in the detection of dynamic objects in a scene without the need for a 3D map or pixel-level map-query correspondences. We contribute an algorithm which refines an initial set of candidate objec... |
FM-Loc: Using Foundation Models for Improved Vision-Based Localization | https://ieeexplore.ieee.org/document/10342439/ | [
"Reihaneh Mirjalili",
"Michael Krawez",
"Wolfram Burgard",
"Reihaneh Mirjalili",
"Michael Krawez",
"Wolfram Burgard"
] | Visual place recognition is essential for vision-based robot localization and SLAM. Despite the tremendous progress made in recent years, place recognition in changing environments remains challenging. A promising approach to cope with appearance variations is to leverage high-level semantic features like objects or place categories. In this paper, we propose FM-Loc which is a novel image-based lo... |
Joint On-Manifold Gravity and Accelerometer Intrinsics Estimation for Inertially Aligned Mapping | https://ieeexplore.ieee.org/document/10342424/ | [
"Ryan Nemiroff",
"Kenny Chen",
"Brett T. Lopez",
"Ryan Nemiroff",
"Kenny Chen",
"Brett T. Lopez"
] | Aligning a robot's trajectory or map to the inertial frame is a critical capability that is often difficult to do accurately even though inertial measurement units (IMUs) can observe absolute roll and pitch with respect to gravity. Accelerometer biases and scale factor errors from the IMU's initial calibration are often the major source of inaccuracies when aligning the robot's odometry frame with... |
I2P-Rec: Recognizing Images on Large-Scale Point Cloud Maps Through Bird's Eye View Projections | https://ieeexplore.ieee.org/document/10341907/ | [
"Shuhang Zheng",
"Yixuan Li",
"Zhu Yu",
"Beinan Yu",
"Si-Yuan Cao",
"Minhang Wang",
"Jintao Xu",
"Rui Ai",
"Weihao Gu",
"Lun Luo",
"Hui-Liang Shen",
"Shuhang Zheng",
"Yixuan Li",
"Zhu Yu",
"Beinan Yu",
"Si-Yuan Cao",
"Minhang Wang",
"Jintao Xu",
"Rui Ai",
"Weihao Gu",
"Lun Luo",
"Hui-Liang Shen"
] | Place recognition is an important technique for autonomous cars to achieve full autonomy since it can provide an initial guess to online localization algorithms. Although current methods based on images or point clouds have achieved satisfactory performance, localizing the images on a large-scale point cloud map remains a fairly unexplored problem. This cross-modal matching task is challenging due... |
LIO-PPF: Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking | https://ieeexplore.ieee.org/document/10341524/ | [
"Xingyu Chen",
"Peixi Wu",
"Ge Li",
"Thomas H. Li",
"Xingyu Chen",
"Peixi Wu",
"Ge Li",
"Thomas H. Li"
] | As a crucial infrastructure of intelligent mobile robots, LiDAR-Inertial odometry (LIO) provides the basic capability of state estimation by tracking LiDAR scans. The high-accuracy tracking generally involves the $k\text{NN}$ search, which is used with minimizing the point-to-plane distance. The cost for this, however, is maintaining a large local map and performing $k\text{NN}$ plane fit for each... |
EDI: ESKF-based Disjoint Initialization for Visual-Inertial SLAM Systems | https://ieeexplore.ieee.org/document/10342106/ | [
"Weihan Wang",
"Jiani Li",
"Yuhang Ming",
"Philippos Mordohai",
"Weihan Wang",
"Jiani Li",
"Yuhang Ming",
"Philippos Mordohai"
] | Visual-inertial initialization can be classified into joint and disjoint approaches. Joint approaches tackle both the visual and the inertial parameters together by aligning observations from feature-bearing points based on IMU integration then use a closed-form solution with visual and acceleration observations to find initial velocity and gravity. In contrast, disjoint approaches independently s... |
SELVO: A Semantic-Enhanced Lidar-Visual Odometry | https://ieeexplore.ieee.org/document/10341419/ | [
"Kun Jiang",
"Shuang Gao",
"Xudong Zhang",
"Jijunnan Li",
"Yandong Guo",
"Shijie Liu",
"Chunlai Li",
"Jianyu Wang",
"Kun Jiang",
"Shuang Gao",
"Xudong Zhang",
"Jijunnan Li",
"Yandong Guo",
"Shijie Liu",
"Chunlai Li",
"Jianyu Wang"
] | In the face of complex external environment, single sensor information can no longer meet the accuracy requirements of low-drift SLAM. In this paper, we focus on the fusion scheme of cameras and lidar, and explore the gain of semantic information to SLAM system. A Semantic-Enhanced Lidar-Visual Odometry (SELVO) is proposed to achieve pose estimation with high accuracy and robustness by applying se... |
LIWO: LiDAR-Inertial-Wheel Odometry | https://ieeexplore.ieee.org/document/10342258/ | [
"Zikang Yuan",
"Fengtian Lang",
"Tianle Xu",
"Xin Yang",
"Zikang Yuan",
"Fengtian Lang",
"Tianle Xu",
"Xin Yang"
] | LiDAR-inertial odometry (LIO), which fuses complementary information of a LiDAR and an Inertial Measurement Unit (IMU), is an attractive solution for state estimation. In LIO, both pose and velocity are regarded as state variables that need to be solved. However, the widely-used Iterative Closest Point (ICP) algorithm can only provide constraint for pose, while the velocity can only be constrained... |
VIW-Fusion: Extrinsic Calibration and Pose Estimation for Visual-IMU-Wheel Encoder System | https://ieeexplore.ieee.org/document/10341453/ | [
"Chunxiao Qiao",
"Shuying Zhao",
"Yunzhou Zhang",
"Yahui Wang",
"Dan Zhang",
"Chunxiao Qiao",
"Shuying Zhao",
"Yunzhou Zhang",
"Yahui Wang",
"Dan Zhang"
] | The data fusion of camera, IMU, and wheel encoder measurements has proved its effectiveness in localizing ground robots, and obtaining accurate sensor extrinsic parameters is its premise. We propose an extrinsic parameter calibration algorithm and a multi-sensor-based pose estimation algorithm for the camera-IMU-wheel encoder system. First, we propose a joint calibration algorithm for the extrinsi... |
LiDAR-Inertial SLAM with Efficiently Extracted Planes | https://ieeexplore.ieee.org/document/10342325/ | [
"Chao Chen",
"Hangyu Wu",
"Yukai Ma",
"Jiajun Lv",
"Laijian Li",
"Yong Liu",
"Chao Chen",
"Hangyu Wu",
"Yukai Ma",
"Jiajun Lv",
"Laijian Li",
"Yong Liu"
] | This paper proposes a LiDAR-Inertial SLAM with efficiently extracted planes, which couples explicit planes in the odometry to improve accuracy and in the mapping for consistency. The proposed method consists of three parts: an efficient Point $\boldsymbol{\rightarrow\text{Line}\rightarrow \text{Plane}}$ extraction algorithm, a LiDAR-Inertial-Plane tightly coupled odometry, and a global plane-aided... |
Learning to Map Efficiently by Active Echolocation | https://ieeexplore.ieee.org/document/10341664/ | [
"Xixi Hu",
"Senthil Purushwalkam",
"David Harwath",
"Kristen Grauman",
"Xixi Hu",
"Senthil Purushwalkam",
"David Harwath",
"Kristen Grauman"
] | Using visual SLAM to map new environments requires time-consuming visits to all regions for data collection. We propose an approach to estimate maps of areas beyond the visible regions using a cheap and readily available modality of data-sound. We introduce the idea of an active audio-visual mapping agent. Besides collecting visual data, the proposed agent emits sounds during navigation, captures ... |
Visual-LiDAR-Inertial Odometry: A New Visual-Inertial SLAM Method Based on an iPhone 12 Pro | https://ieeexplore.ieee.org/document/10341536/ | [
"Lingqiu Jin",
"Cang Ye",
"Lingqiu Jin",
"Cang Ye"
] | As today's smartphone integrates various imaging sensors and Inertial Measurement Units (IMU) and becomes computationally powerful, there is a growing interest in developing smartphone-based visual-inertial (VI) SLAM methods for robotics and computer vision applications. In this paper, we introduce a new SLAM method, called Visual-LiDAR-Inertial Odometry (VLIO), based on an iPhone 12 Pro. VLIO for... |
Optimization-Based VINS: Consistency, Marginalization, and FEJ | https://ieeexplore.ieee.org/document/10341637/ | [
"Chuchu Chen",
"Patrick Geneva",
"Yuxiang Peng",
"Woosik Lee",
"Guoquan Huang",
"Chuchu Chen",
"Patrick Geneva",
"Yuxiang Peng",
"Woosik Lee",
"Guoquan Huang"
] | In this work, we present a comprehensive analysis of the application of the First-estimates Jacobian (FEJ) design methodology in nonlinear optimization-based Visual-Inertial Navigation Systems (VINS). The FEJ approach fixes system linearization points to preserve proper observability properties of VINS and has been shown to significantly improve the estimation performance of state-of-the-art filte... |
Visual-Inertial-Laser-Lidar (VILL) SLAM: Real-Time Dense RGB-D Mapping for Pipe Environments | https://ieeexplore.ieee.org/document/10341761/ | [
"Tina Tian",
"Luyuan Wang",
"Xinzhi Yan",
"Fujun Ruan",
"G. Jaya Aadityaa",
"Howie Choset",
"Lu Li",
"Tina Tian",
"Luyuan Wang",
"Xinzhi Yan",
"Fujun Ruan",
"G. Jaya Aadityaa",
"Howie Choset",
"Lu Li"
] | Robotic solutions for pipeline inspection promise enhancement of human labor by automating data acquisition for pipe condition assessments, which are vital for the early detection of pipe anomalies and the prevention of hazardous leakages and explosions. Through simultaneous localization and mapping (SLAM), colorized 3D reconstructions of the pipe's inner surface can be generated, providing a more... |
Joint Imitation Learning of Behavior Decision and Control for Autonomous Intersection Navigation | https://ieeexplore.ieee.org/document/10342405/ | [
"Zeyu Zhu",
"Huijing Zhao",
"Zeyu Zhu",
"Huijing Zhao"
] | Modern autonomous driving systems face substantial challenges when navigating dense intersections due to the high uncertainty introduced by other road users. Due to the complexity of the task, the autonomous vehicle needs to generate policies at multiple levels of abstraction. However, previous deep imitation learning methods focused on learning control policies while using simple rule-based behav... |
Improving the Performance of Backward Chained Behavior Trees that use Reinforcement Learning | https://ieeexplore.ieee.org/document/10342319/ | [
"Mart Kartasev",
"Justin Salér",
"Petter Ögren",
"Mart Kartasev",
"Justin Salér",
"Petter Ögren"
] | In this paper we show how to improve the performance of backward chained behavior trees (BTs) that include policies trained with reinforcement learning (RL). BTs represent a hierarchical and modular way of combining control policies into higher level control policies. Backward chaining is a design principle for the construction of BTs that combines reactivity with goal directed actions in a struct... |
Fast Decision Support for Air Traffic Management at Urban Air Mobility Vertiports Using Graph Learning | https://ieeexplore.ieee.org/document/10341398/ | [
"Prajit KrisshnaKumar",
"Jhoel Witter",
"Steve Paul",
"Hanvit Cho",
"Karthik Dantu",
"Souma Chowdhury",
"Prajit KrisshnaKumar",
"Jhoel Witter",
"Steve Paul",
"Hanvit Cho",
"Karthik Dantu",
"Souma Chowdhury"
] | Urban Air Mobility (UAM) promises a new dimension to decongested, safe, and fast travel in urban and suburban hubs. These UAM aircraft are conceived to operate from small airports called vertiports each comprising multiple take-offllanding and battery-recharging spots. Since they might be situated in dense urban areas and need to handle many aircraft landings and take-offs each hour, managing this... |
Scaling Vision-Based End-to-End Autonomous Driving with Multi-View Attention Learning | https://ieeexplore.ieee.org/document/10341506/ | [
"Yi Xiao",
"Felipe Codevilla",
"Diego Porres",
"Antonio M. López",
"Yi Xiao",
"Felipe Codevilla",
"Diego Porres",
"Antonio M. López"
] | On end-to-end driving, human driving demonstrations are used to train perception-based driving models by imitation learning. This process is supervised on vehicle signals (e.g., steering angle, acceleration) but does not require extra costly supervision (human labeling of sensor data). As a representative of such vision-based end-to-end driving models, CILRS is commonly used as a baseline to compa... |
Value of Assistance for Mobile Agents | https://ieeexplore.ieee.org/document/10342313/ | [
"Adi Amuzig",
"David Dovrat",
"Sarah Keren",
"Adi Amuzig",
"David Dovrat",
"Sarah Keren"
] | Mobile robotic agents often suffer from localization uncertainty which grows with time and with the agents' movement. This can hinder their ability to accomplish their task. In some settings, it may be possible to perform assistive actions that reduce uncertainty about a robot's location. For example, in a collaborative multi-robot system, a wheeled robot can request assistance from a drone that c... |
Feature Explanation for Robust Trajectory Prediction | https://ieeexplore.ieee.org/document/10341825/ | [
"Xukai Zhai",
"Renze Hu",
"Zhishuai Yin",
"Xukai Zhai",
"Renze Hu",
"Zhishuai Yin"
] | Trajectory prediction of neighboring agents is a critical task for high-speed robotics such as autonomous vehicles. In order to obtain fine-grained and robust scene representations, existing works attempt to consider abundant information that is deemed relevant. The cost, however, is the heavy computational burden and more importantly the inevitable interference brought by redundant information. I... |
Adversarial Driving Behavior Generation Incorporating Human Risk Cognition for Autonomous Vehicle Evaluation | https://ieeexplore.ieee.org/document/10341750/ | [
"Zhen Liu",
"Hang Gao",
"Hao Ma",
"Shuo Cai",
"Yunfeng Hu",
"Ting Qu",
"Hong Chen",
"Xun Gong",
"Zhen Liu",
"Hang Gao",
"Hao Ma",
"Shuo Cai",
"Yunfeng Hu",
"Ting Qu",
"Hong Chen",
"Xun Gong"
] | Autonomous vehicle (AV) evaluation has been the subject of increased interest in recent years both in industry and in academia. This paper focuses on the development of a novel framework for generating adversarial driving behavior of background vehicle interfering against the AV to expose effective and rational risky events. Specifically, the adversarial behavior is learned by a reinforcement lear... |
Predicting Center of Mass by Iterative Pushing for Object Transportation and Manipulation | https://ieeexplore.ieee.org/document/10341534/ | [
"Steven M. Hyland",
"Jing Xiao",
"Cagdas D. Onal",
"Steven M. Hyland",
"Jing Xiao",
"Cagdas D. Onal"
] | Robotic manipulation tasks rely on a plethora of environmental and payload information. One critical piece of information for accurate manipulation is the center of mass (CoM) of the object, which is essential for estimating the dynamic response of the system and determining the payload placement. Traditionally, the CoM of a payload is provided prior to manipulation. In order to create a more robu... |
The Impact of Overall Optimization on Warehouse Automation | https://ieeexplore.ieee.org/document/10342333/ | [
"Hiroshi Yoshitake",
"Pieter Abbeel",
"Hiroshi Yoshitake",
"Pieter Abbeel"
] | In this study, we propose a novel approach for investigating optimization performance by flexible robot co-ordination in automated warehouses with multi-agent rein-forcement learning (MARL)-based control. Automated systems using robots are expected to achieve efficient operations compared with manual systems in terms of overall optimization performance. However, the impact of overall optimization ... |
Kinematics-Only Differential Flatness Based Trajectory Tracking for Autonomous Racing | https://ieeexplore.ieee.org/document/10341603/ | [
"Yashom Dighe",
"Youngjin Kim",
"Smit Rajguru",
"Yash Turkar",
"Tarunraj Singh",
"Karthik Dantu",
"Yashom Dighe",
"Youngjin Kim",
"Smit Rajguru",
"Yash Turkar",
"Tarunraj Singh",
"Karthik Dantu"
] | In autonomous racing, accurately tracking the race line at the limits of handling is essential to guarantee competitiveness. In this study, we show the effectiveness of Differential Flatness based control for high-speed trajectory tracking for car-like robots. We compare the tracking performance of our controller against Nonlinear Model Predictive Control and resource use while running on embedded... |
LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection | https://ieeexplore.ieee.org/document/10341958/ | [
"Tong He",
"Pei Sun",
"Zhaoqi Leng",
"Chenxi Liu",
"Dragomir Anguelov",
"Mingxing Tan",
"Tong He",
"Pei Sun",
"Zhaoqi Leng",
"Chenxi Liu",
"Dragomir Anguelov",
"Mingxing Tan"
] | We propose a late-to-early recurrent feature fusion scheme for 3D object detection using temporal LiDAR point clouds. Our main motivation is fusing object-aware latent embeddings into the early stages of a 3D object detector. This feature fusion strategy enables the model to better capture the shapes and poses for challenging objects, compared with learning from raw points directly. Our method con... |
Hierarchical Decision Transformer | https://ieeexplore.ieee.org/document/10342230/ | [
"André Correia",
"Luis A. Alexandre",
"André Correia",
"Luis A. Alexandre"
] | Sequence models in reinforcement learning require task knowledge to estimate the task policy. This paper presents the hierarchical decision transformer (HDT). HDT is a hierarchical behavior cloning algorithm that improves the performance of transformer methods in imitation learning, improving their robustness to tasks with longer episodes and/or sparse rewards, without requiring task knowledge or ... |
Imitation-Guided Multimodal Policy Generation from Behaviourally Diverse Demonstrations | https://ieeexplore.ieee.org/document/10341403/ | [
"Shibei Zhu",
"Rituraj Kaushik",
"Samuel Kaski",
"Ville Kyrki",
"Shibei Zhu",
"Rituraj Kaushik",
"Samuel Kaski",
"Ville Kyrki"
] | Learning policies from multiple demonstrators is often difficult because different individuals perform the same task differently due to hidden factors such as preferences. In the context of policy learning, this leads to multimodal policies. Existing policy learning methods often converge to a single solution mode, failing to capture the diversity in the solution space. In this paper, we introduce... |
Model-based Adversarial Imitation Learning from Demonstrations and Human Reward | https://ieeexplore.ieee.org/document/10341411/ | [
"Jie Huang",
"Jiangshan Hao",
"Rongshun Juan",
"Randy Gomez",
"Keisuke Nakarnura",
"Guangliang Li",
"Jie Huang",
"Jiangshan Hao",
"Rongshun Juan",
"Randy Gomez",
"Keisuke Nakarnura",
"Guangliang Li"
] | Reinforcement learning (RL) can potentially be applied to real-world robot control in complex and uncertain environments. However, it is difficult or even unpractical to design an efficient reward function for various tasks, especially those large and high-dimensional environments. Generative adversarial imitation learning (GAIL) - a general model-free imitation learning method, allows robots to d... |
Interpretable Motion Planner for Urban Driving via Hierarchical Imitation Learning | https://ieeexplore.ieee.org/document/10342448/ | [
"Bikun Wang",
"Zhipeng Wang",
"Chenhao Zhu",
"Zhiqiang Zhang",
"Zhichen Wang",
"Penghong Lin",
"Jingchu Liu",
"Qian Zhang",
"Bikun Wang",
"Zhipeng Wang",
"Chenhao Zhu",
"Zhiqiang Zhang",
"Zhichen Wang",
"Penghong Lin",
"Jingchu Liu",
"Qian Zhang"
] | Learning-based approaches have achieved remarkable performance in the domain of autonomous driving. Leveraging the impressive ability of neural networks and large amounts of human driving data, complex patterns and rules of driving behavior can be encoded as a model to benefit the autonomous driving system. Besides, an increasing number of data-driven works have been studied in the decision-making... |
Hierarchical Imitation Learning for Stochastic Environments | https://ieeexplore.ieee.org/document/10341451/ | [
"Maximilian Igl",
"Punit Shah",
"Paul Mougin",
"Sirish Srinivasan",
"Tarun Gupta",
"Brandyn White",
"Kyriacos Shiarlis",
"Shimon Whiteson",
"Maximilian Igl",
"Punit Shah",
"Paul Mougin",
"Sirish Srinivasan",
"Tarun Gupta",
"Brandyn White",
"Kyriacos Shiarlis",
"Shimon Whiteson"
] | Many applications of imitation learning require the agent to generate the full distribution of behaviour observed in the training data. For example, to evaluate the safety of autonomous vehicles in simulation, accurate and diverse behaviour models of other road users are paramount. Existing methods that improve this distributional realism typically rely on hierarchical policies. These condition th... |
Efficient Deep Learning of Robust, Adaptive Policies using Tube MPC-Guided Data Augmentation | https://ieeexplore.ieee.org/document/10341998/ | [
"Tong Zhao",
"Andrea Tagliabue",
"Jonathan P. How",
"Tong Zhao",
"Andrea Tagliabue",
"Jonathan P. How"
] | The deployment of agile autonomous systems in challenging, unstructured environments requires adaptation capabilities and robustness to uncertainties. Existing robust and adaptive controllers, such as those based on model predictive control (MPC), can achieve impressive performance at the cost of heavy online onboard computations. Strategies that efficiently learn robust and onboard-deployable pol... |
Masked Imitation Learning: Discovering Environment-Invariant Modalities in Multimodal Demonstrations | https://ieeexplore.ieee.org/document/10341728/ | [
"Yilun Hao",
"Ruinan Wang",
"Zhangjie Cao",
"Zihan Wang",
"Yuchen Cui",
"Dorsa Sadigh",
"Yilun Hao",
"Ruinan Wang",
"Zhangjie Cao",
"Zihan Wang",
"Yuchen Cui",
"Dorsa Sadigh"
] | Multimodal demonstrations provide robots with an abundance of information to make sense of the world. However, such abundance may not always lead to good performance when it comes to learning sensorimotor control policies from human demonstrations. Extraneous data modalities can lead to state over-specification, where the state contains modalities that are not only useless for decision-making but ... |
Does Unpredictability Influence Driving Behavior? | https://ieeexplore.ieee.org/document/10342534/ | [
"Sepehr Samavi",
"Florian Shkurti",
"Angela P. Schoellig",
"Sepehr Samavi",
"Florian Shkurti",
"Angela P. Schoellig"
] | In this paper we investigate the effect of the unpredictability of surrounding cars on an ego-car performing a driving maneuver. We use Maximum Entropy Inverse reinforcement Learning to model reward functions for an ego-car conducting a lane change in a highway setting. We define a new feature based on the unpredictability of surrounding cars and use it in the reward function. We learn two reward ... |
From Temporal-Evolving to Spatial-Fixing: A Keypoints-Based Learning Paradigm for Visual Robotic Manipulation | https://ieeexplore.ieee.org/document/10341397/ | [
"Kevin Riou",
"Kaiwen Dong",
"Kevin Subrin",
"Yanjing Sun",
"Patrick Le Callet",
"Kevin Riou",
"Kaiwen Dong",
"Kevin Subrin",
"Yanjing Sun",
"Patrick Le Callet"
] | The current learning pipelines for robotics manipulation infer movement primitives sequentially along the temporal-evolving axis, which can result in an accumulation of prediction errors and subsequently cause the visual observations to fall out of the training distribution. This paper proposes a novel hierarchical behavior cloning approach which tries to dissociate standard behaviour cloning (BC)... |
Accurate and Interactive Visual-Inertial Sensor Calibration with Next-Best-View and Next-Best-Trajectory Suggestion | https://ieeexplore.ieee.org/document/10341815/ | [
"Christopher L. Choi",
"Binbin Xu",
"Stefan Leutenegger",
"Christopher L. Choi",
"Binbin Xu",
"Stefan Leutenegger"
] | Visual-Inertial (VI) sensors are popular in robotics, self-driving vehicles, and augmented and virtual reality applications. In order to use them for any computer vision or state-estimation task, a good calibration is essential. However, collecting informative calibration data in order to render the calibration parameters observable is not trivial for a non-expert. In this work, we introduce a nov... |
A ROS-Based Kinematic Calibration Tool for Serial Robots | https://ieeexplore.ieee.org/document/10341692/ | [
"Caroline Pascal",
"Olivier Doaré",
"Alexandre Chapoutot",
"Caroline Pascal",
"Olivier Doaré",
"Alexandre Chapoutot"
] | The use of serial robots for industrial and research purposes is often limited by a flawed positioning accuracy, caused by the differences between the robot nominal model, and the real one. Such an issue can be solved by means of kinematic calibration, which is usually a tedious and intricate task. In this paper, we propose a complete kinematic calibration procedure relying on established geometri... |
FUSE-D: Framework for UAV System-Parameter Estimation with Disturbance Detection | https://ieeexplore.ieee.org/document/10341818/ | [
"Christoph Böhm",
"Stephan Weiss",
"Christoph Böhm",
"Stephan Weiss"
] | Modern unmanned aerial vehicles (UAVs) with sophisticated mechanics ask for extended online system identification to aid model-based controls in task execution. In addition, UAVs in adverse environmental conditions require a more detailed environmental disturbance understanding. The necessary combination of online system identification, sensor suite self-calibration, and external disturbance analy... |
Multiplanar Self-Calibration for Mobile Cobot 3D Object Manipulation Using 2D Detectors and Depth Estimation | https://ieeexplore.ieee.org/document/10341911/ | [
"Tuan Dang",
"Khang Nguyen",
"Manfred Huber",
"Tuan Dang",
"Khang Nguyen",
"Manfred Huber"
] | Calibration is the first and foremost step in dealing with sensor displacement errors that can appear during extended operation and off-time periods to enable robot object manipulation with precision. In this paper, we present a novel multiplanar self-calibration between the camera system and the robot's end-effector for 3D object manipulation. Our approach first takes the robot end-effector as gr... |
Labelling Lightweight Robot Energy Consumption: A Mechatronics-Based Benchmarking Metric Set | https://ieeexplore.ieee.org/document/10341484/ | [
"Juan Heredia",
"Robin Jeanne Kirschner",
"Christian Schlette",
"Saeed Abdolshah",
"Sami Haddadin",
"Mikkel Baun Kjærgaard",
"Juan Heredia",
"Robin Jeanne Kirschner",
"Christian Schlette",
"Saeed Abdolshah",
"Sami Haddadin",
"Mikkel Baun Kjærgaard"
] | Compliance with global guidelines for sustainable and responsible production in modern industry requires a comparative analysis of consumer devices' energy consumption (EC). This also holds true for the newly established generation of lightweight industrial robots (LIRs). To identify potential strategies for energy optimization, standardized benchmarking procedures are required. However, to the be... |
The Role of Absolute Positioning Error in Hand-Eye Calibration and Robotic Guidance Systems: An Analysis | https://ieeexplore.ieee.org/document/10342337/ | [
"Michal Chaluš",
"Ondřej Vaníček",
"Jindřich Liška",
"Michal Chaluš",
"Ondřej Vaníček",
"Jindřich Liška"
] | Robotic manipulators deal with serious issues due to their absolute positioning error. This error is usually compensated by an operator in classical robot programming using the teach-and-play method. However, it has a significant effect on accuracy of robotic guidance systems (RGS) that automatically generate process tool trajectory based on the measured data from a sensor. In this paper, we first... |
Robotic Kinematic Calibration with Only Position Data and Consideration of Non-Geometric Errors Using POE-Based Model and Gaussian Mixture Models | https://ieeexplore.ieee.org/document/10341731/ | [
"Xiao Luo",
"Yitian Xian",
"Mancheong Lei",
"Jian Li",
"Ke Xie",
"Limin Zou",
"Zheng Li",
"Xiao Luo",
"Yitian Xian",
"Mancheong Lei",
"Jian Li",
"Ke Xie",
"Limin Zou",
"Zheng Li"
] | Kinematic calibration is crucial to improve the positioning accuracy of serial robots. This paper proposes a novel algorithm for robotic kinematic calibration based on an augmented product of exponentials (POE)-based kinematic model using Gaussian mixture models (GMMs) with only position data. In this algorithm, non-geometric errors that cannot be fitted by varying the parameters within the tradit... |
MOISST: Multimodal Optimization of Implicit Scene for SpatioTemporal Calibration | https://ieeexplore.ieee.org/document/10342427/ | [
"Quentin Herau",
"Nathan Piasco",
"Moussab Bennehar",
"Luis Roldão",
"Dzmitry Tsishkou",
"Cyrille Migniot",
"Pascal Vasseur",
"Cédric Demonceaux",
"Quentin Herau",
"Nathan Piasco",
"Moussab Bennehar",
"Luis Roldão",
"Dzmitry Tsishkou",
"Cyrille Migniot",
"Pascal Vasseur",
"Cédric Demonceaux"
] | With the recent advances in autonomous driving and the decreasing cost of LiDARs, the use of multimodal sensor systems is on the rise. However, in order to make use of the information provided by a variety of complimentary sensors, it is necessary to accurately calibrate them. We take advantage of recent advances in computer graphics and implicit volumetric scene representation to tackle the probl... |
Automatic Spatial Radar Camera Calibration via Geometric Constraints with Doppler-Optical Flow Fusion | https://ieeexplore.ieee.org/document/10342101/ | [
"Jintian Ge",
"Yanxin Zhou",
"Baichuan Lou",
"Chen Lv",
"Jintian Ge",
"Yanxin Zhou",
"Baichuan Lou",
"Chen Lv"
] | Many intelligent robots use a combination of radar and camera sensors to capture environmental information. Robust and accurate perception highly relies on the result of multi-sensor calibration. Most current spatial calibration methods require a calibration board or a special marker as the target. In this paper, we provide a novel calibration method for RGBD camera and millimeter-wave radar, whic... |
Extrinsic Calibration of Camera to LIDAR Using a Differentiable Checkerboard Model | https://ieeexplore.ieee.org/document/10341781/ | [
"Lanke Frank Tarimo Fu",
"Nived Chebrolu",
"Maurice Fallon",
"Lanke Frank Tarimo Fu",
"Nived Chebrolu",
"Maurice Fallon"
] | Multi-modal sensing often involves determining correspondences between each domain's signals, which in turn depends on the accurate extrinsic calibration of the sensors. Challengingly, the camera-LIDAR sensor modalities are quite dissimilar and the narrow field of view of most commercial LIDARs means that they observe only a partial view of the camera frustum. We present a framework for extrinsic ... |
Graph-Based Visual-Kinematic Fusion and Monte Carlo Initialization for Fast-Deployable Cable-Driven Robots | https://ieeexplore.ieee.org/document/10342316/ | [
"R. Khorrambakht",
"H. Damirchi",
"M.R. Dindarloo",
"A. Saki",
"S.A. Khalilpour",
"Hamid D. Taghirad",
"Stephan Weiss",
"R. Khorrambakht",
"H. Damirchi",
"M.R. Dindarloo",
"A. Saki",
"S.A. Khalilpour",
"Hamid D. Taghirad",
"Stephan Weiss"
] | Ease of calibration and high-accuracy task-space state-estimation purely based on onboard sensors is a key requirement for enabling easily deployable cable robots in real-world applications. In this work, we incorporate the onboard camera and kinematic sensors to drive a statistical fusion framework that presents a unified localization and calibration system which requires no initial values for th... |
P2O-Calib: Camera-LiDAR Calibration Using Point-Pair Spatial Occlusion Relationship | https://ieeexplore.ieee.org/document/10341416/ | [
"Su Wang",
"Shini Zhang",
"Xuchong Qiu",
"Su Wang",
"Shini Zhang",
"Xuchong Qiu"
] | The accurate and robust calibration result of sensors is considered as an important building block to the follow-up research in the autonomous driving and robotics domain. The current works involving extrinsic calibration between 3D LiDARs and monocular cameras mainly focus on target-based and target-less methods. The target-based methods are often utilized offline because of restrictions, such as... |
Wrench Estimation of Modular Manipulator with External Actuation and Joint Locking | https://ieeexplore.ieee.org/document/10341887/ | [
"Yonghyeok Kim",
"Hasun Lee",
"Jeongseob Lee",
"Dongjun Lee",
"Yonghyeok Kim",
"Hasun Lee",
"Jeongseob Lee",
"Dongjun Lee"
] | This paper proposes an external wrench estimation method for modular manipulators, where each link module is driven with external actuation (e.g., rotors, thrusters) and inter-module joints can be locked to increase end-effector stiffness or workforce of the manipulator. For such systems, the commonly-used momentum-based observer (MBO [1]) is not suitable due to the presence of unknown joint locki... |
AV-PedAware: Self-Supervised Audio-Visual Fusion for Dynamic Pedestrian Awareness | https://ieeexplore.ieee.org/document/10342257/ | [
"Yizhuo Yang",
"Shenghai Yuan",
"Muqing Cao",
"Jianfei Yang",
"Lihua Xie",
"Yizhuo Yang",
"Shenghai Yuan",
"Muqing Cao",
"Jianfei Yang",
"Lihua Xie"
] | In this study, we introduce AV-PedAware, a self-supervised audio-visual fusion system designed to improve dynamic pedestrian awareness for robotics applications. Pedestrian awareness is a critical requirement in many robotics applications. However, traditional approaches that rely on cameras and LIDARs to cover multiple views can be expensive and susceptible to issues such as changes in illuminati... |
A Multitask and Kernel Approach for Learning to Push Objects with a Target-Parameterized Deep Q-Network | https://ieeexplore.ieee.org/document/10341729/ | [
"Marco Ewerton",
"Michael Villamizar",
"Julius Jankowski",
"Sylvain Calinon",
"Jean-Marc Odobez",
"Marco Ewerton",
"Michael Villamizar",
"Julius Jankowski",
"Sylvain Calinon",
"Jean-Marc Odobez"
] | Pushing is an essential motor skill involved in several manipulation tasks, and has been an important research topic in robotics. Recent works have shown that Deep Q-Networks (DQNs) can learn pushing policies (when, where to push, and how) to solve manipulation tasks, potentially in synergy with other skills (e.g. grasping). Nevertheless, DQNs often assume a fixed setting and task, which may limit... |
DRKF: Distilled Rotated Kernel Fusion for Efficient Rotation Invariant Descriptors in Local Feature Matching | https://ieeexplore.ieee.org/document/10341994/ | [
"Ranran Huang",
"Jiancheng Cai",
"Chao Li",
"Zhuoyuan Wu",
"Xinmin Liu",
"Zhenhua Chai",
"Ranran Huang",
"Jiancheng Cai",
"Chao Li",
"Zhuoyuan Wu",
"Xinmin Liu",
"Zhenhua Chai"
] | The performance of local feature descriptors degrades in the presence of large rotation variations. To address this issue, we present an efficient approach to learning rotation invariant descriptors. Specifically, we propose Rotated Kernel Fusion (RKF) which imposes rotations on the convolution kernel to improve the inherent nature of CNN. Since RKF can be processed by the subsequent re-parameteri... |
Efficient Q-Learning over Visit Frequency Maps for Multi-Agent Exploration of Unknown Environments | https://ieeexplore.ieee.org/document/10341899/ | [
"Xuyang Chen",
"Ashvin N. Iyer",
"Zixing Wang",
"Ahmed H. Qureshi",
"Xuyang Chen",
"Ashvin N. Iyer",
"Zixing Wang",
"Ahmed H. Qureshi"
] | The robot exploration task has been widely studied with applications spanning from novel environment mapping to item delivery. For some time-critical tasks, such as rescue catastrophes, the agent is required to explore as efficiently as possible. Recently, Visit Frequency-based map representation achieved great success in such scenarios by discouraging repetitive visits with a frequency-based pena... |
Real-Time Trajectory-Based Social Group Detection | https://ieeexplore.ieee.org/document/10342121/ | [
"Simindokht Jahangard",
"Munawar Hayat",
"Hamid Rezatofighi",
"Simindokht Jahangard",
"Munawar Hayat",
"Hamid Rezatofighi"
] | Social group detection is a crucial aspect of various robotic applications, including robot navigation and human-robot interactions. To date, a range of model-based techniques have been employed to address this challenge, such as the F-formation and trajectory similarity frameworks. However, these approaches often fail to provide reliable results in crowded and dynamic scenarios. Recent advancemen... |
Point2Point: A Framework for Efficient Deep Learning on Hilbert Sorted Point Clouds with Applications in Spatio-Temporal Occupancy Prediction | https://ieeexplore.ieee.org/document/10341640/ | [
"Athrva Atul Pandhare",
"Athrva Atul Pandhare"
] | The irregularity and permutation invariance of point cloud data pose challenges for effective learning. Conventional methods for addressing this issue involve converting raw point clouds to intermediate representations such as 3D voxel grids or range images. While such intermediate representations solve the problem of permutation invariance, they can result in significant loss of information. Appr... |
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models | https://ieeexplore.ieee.org/document/10342382/ | [
"João Carvalho",
"An T. Le",
"Mark Baierl",
"Dorothea Koert",
"Jan Peters",
"João Carvalho",
"An T. Le",
"Mark Baierl",
"Dorothea Koert",
"Jan Peters"
] | Learning priors on trajectory distributions can help accelerate robot motion planning optimization. Given previously successful plans, learning trajectory generative models as priors for a new planning problem is highly desirable. Prior works propose several ways on utilizing this prior to bootstrapping the motion planning problem. Either sampling the prior for initializations or using the prior d... |
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