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A Visibility-Based Escort Problem | https://ieeexplore.ieee.org/document/10341574/ | [
"Lance G. Fletcher",
"Priyankari Perali",
"Andrew Beathard",
"Jason M. O'Kane",
"Lance G. Fletcher",
"Priyankari Perali",
"Andrew Beathard",
"Jason M. O'Kane"
] | This paper introduces and solves a visibility-based escort planning problem. This novel problem, which is closely related to the well-researched family of visibility-based pursuit-evasion problems in robotics, entails an escort agent tasked with escorting a vulnerable agent, called the VIP, in a 2-dimensional environment. The escort protects the VIP from adversaries that pose line-of-sight threats... |
Enhancing Value Estimation Policies by Post-Hoc Symmetry Exploitation in Motion Planning Tasks | https://ieeexplore.ieee.org/document/10341746/ | [
"Yazied Hasan",
"Ariana M. Villegas-Suarez",
"Evan C. Carter",
"Aleksandra Faust",
"Lydia Tapia",
"Yazied Hasan",
"Ariana M. Villegas-Suarez",
"Evan C. Carter",
"Aleksandra Faust",
"Lydia Tapia"
] | Motion planning tasks are often innately invariant to certain geometric transformations, or in other words, symmetric. This property, however, is not always reflected in learned policies that are trained on these tasks. Although this asymmetry can be addressed through data augmentation or additional training samples, doing so comes at a cost of increased training time. Instead of trying to remedy ... |
Risk-Aware Emergency Landing Planning for Gliding Aircraft Model in Urban Environments | https://ieeexplore.ieee.org/document/10341622/ | [
"Jakub Sláma",
"Jáchym Herynek",
"Jan Faigl",
"Jakub Sláma",
"Jáchym Herynek",
"Jan Faigl"
] | An in-flight loss of thrust poses a risk to the aircraft, its passengers, and people on the ground. When a loss of thrust happens, the (auto)pilot is forced to perform an emergency landing, possibly toward one of the reachable airports. If none of the airports is reachable, the aircraft is forced to land at another location, which can be risky in urban environments. In this work, we present a gene... |
SCTOMP: Spatially Constrained Time-Optimal Motion Planning | https://ieeexplore.ieee.org/document/10341500/ | [
"Jon Arrizabalaga",
"Markus Ryll",
"Jon Arrizabalaga",
"Markus Ryll"
] | This work focuses on spatial time-optimal motion planning, a generalization of the exact time-optimal path following problem that allows a system to plan within a predefined space. In contrast to state-of-the-art methods, we drop the assumption of a given collision-free geometric reference. Instead, we present a three-stage motion planning method that solely relies on start and goal locations and ... |
Consecutive Inertia Drift of Autonomous RC Car via Primitive-Based Planning and Data-Driven Control | https://ieeexplore.ieee.org/document/10341461/ | [
"Yiwen Lu",
"Bo Yang",
"Jiayun Li",
"Yihan Zhou",
"Hongshuai Chen",
"Yilin Mo",
"Yiwen Lu",
"Bo Yang",
"Jiayun Li",
"Yihan Zhou",
"Hongshuai Chen",
"Yilin Mo"
] | Inertia drift is an aggressive transitional driving maneuver, which is challenging due to the high nonlinearity of the system and the stringent requirement on control and planning performance. This paper presents a solution for the consecutive inertia drift of an autonomous RC car based on primitive-based planning and data-driven control. The planner generates complex paths via the concatenation o... |
A Hybrid-State Path Planner for ASV Formations with Full-Scale Experiments | https://ieeexplore.ieee.org/document/10341696/ | [
"Else-Line M. Ruud",
"Marius S. Rundhovde",
"Jarle Sandrib",
"Glenn Bitar",
"Else-Line M. Ruud",
"Marius S. Rundhovde",
"Jarle Sandrib",
"Glenn Bitar"
] | We present a hybrid-state path planner for autonomous surface vehicles (ASVs) constrained by a min-imum turning radius. The work is motivated by the future Norwegian naval mine countermeasures (NMCM) concept, which includes mine sweeping operations with ASVs that operate alone or in a formation of two, with and without mine sweeping equipment attached. Our path-planning approach is a variant of hy... |
CAT-RRT: Motion Planning that Admits Contact One Link at a Time | https://ieeexplore.ieee.org/document/10341668/ | [
"Nataliya Nechyporenko",
"Caleb Escobedo",
"Shreyas Kadekodi",
"Alessandro Roncone",
"Nataliya Nechyporenko",
"Caleb Escobedo",
"Shreyas Kadekodi",
"Alessandro Roncone"
] | Current motion planning approaches rely on binary collision checking to evaluate the validity of a state and thereby dictate where the robot is allowed to move. This approach leaves little room for robots to engage in contact with an object, as is often necessary when operating in densely cluttered spaces. In this work, we propose an alternative method that considers contact states as high-cost st... |
Novel Gripper with Rotatable Distal Joints for Home Robots: Picking and Placing Tableware | https://ieeexplore.ieee.org/document/10342249/ | [
"Sung-Woo Kim",
"Cheog gyu Hwang",
"Sunkyum Yoo",
"Youngdae Ko",
"Sungchul Kang",
"Sung-Woo Kim",
"Cheog gyu Hwang",
"Sunkyum Yoo",
"Youngdae Ko",
"Sungchul Kang"
] | A convenient situation can be realized if home robots replace housework. However, tasks in an actual home environment are challenging for robots. Particularly, cleaning the table after eating is challenging because of the cluttered environments and various tableware shapes. This study presents a new type of gripper appropriate for picking and placing various tableware in narrow and cluttered envir... |
Prioritized Planning for Target-Oriented Manipulation via Hierarchical Stacking Relationship Prediction | https://ieeexplore.ieee.org/document/10342196/ | [
"Zewen Wu",
"Jian Tang",
"Xingyu Chen",
"Chengzhong Ma",
"Xuguang Lan",
"Nanning Zheng",
"Zewen Wu",
"Jian Tang",
"Xingyu Chen",
"Chengzhong Ma",
"Xuguang Lan",
"Nanning Zheng"
] | In scenarios involving grasping multiple targets, the learning of stacking relationships between objects is fundamental for robots to execute safely and efficiently. However, current methods lack subdivision for the hierarchy of stacking relationship types. In scenes where objects are mostly stacked in an orderly manner, they are incapable of performing human-like and high-efficient grasping decis... |
Task-Oriented Grasp Prediction with Visual-Language Inputs | https://ieeexplore.ieee.org/document/10342268/ | [
"Chao Tang",
"Dehao Huang",
"Lingxiao Meng",
"Weiyu Liu",
"Hong Zhang",
"Chao Tang",
"Dehao Huang",
"Lingxiao Meng",
"Weiyu Liu",
"Hong Zhang"
] | To perform household tasks, assistive robots receive commands in the form of user language instructions for tool manipulation. The initial stage involves selecting the intended tool (i.e., object grounding) and grasping it in a task-oriented manner (i.e., task grounding). Nevertheless, prior researches on visual-language grasping (VLG) focus on object grounding, while disregarding the fine-grained... |
Learning to Grasp Clothing Structural Regions for Garment Manipulation Tasks | https://ieeexplore.ieee.org/document/10342086/ | [
"Wei Chen",
"Dongmyoung Lee",
"Digby Chappell",
"Nicolas Rojas",
"Wei Chen",
"Dongmyoung Lee",
"Digby Chappell",
"Nicolas Rojas"
] | When performing cloth-related tasks, such as garment hanging, it is often important to identify and grasp certain structural regions—a shirt's collar as opposed to its sleeve, for instance. However, due to cloth deformability, these manipulation activities, which are essential in domestic, health care, and industrial contexts, remain challenging for robots. In this paper, we focus on how to segmen... |
External Sensor-Less in-Hand Object Position Manipulation for an Under-Actuated Hand Using Data-Driven-Based Methods to Compensate for the Nonlinearity of Self-Locking Mechanism | https://ieeexplore.ieee.org/document/10341517/ | [
"Ha Thang Long Doan",
"Hikaru Arita",
"Kenji Tahara",
"Ha Thang Long Doan",
"Hikaru Arita",
"Kenji Tahara"
] | Dexterous manipulation using an under-actuated hand has been a challenging task due to its non-linear dynamical characteristics. For a linkage-based under-actuated hand designed to be used to grasp and manipulate large, heavy, and rigid objects stably, precision grasping is necessary, which makes the task even more difficult to deal with. While approaches based on external sensors have been introd... |
Contact-Aware Shaping and Maintenance of Deformable Linear Objects With Fixtures | https://ieeexplore.ieee.org/document/10341726/ | [
"Kejia Chen",
"Zhenshan Bing",
"Fan Wu",
"Yuan Meng",
"André Kraft",
"Sami Haddadin",
"Alois Knoll",
"Kejia Chen",
"Zhenshan Bing",
"Fan Wu",
"Yuan Meng",
"André Kraft",
"Sami Haddadin",
"Alois Knoll"
] | Studying the manipulation of deformable linear objects has significant practical applications in industry, including car manufacturing, textile production, and electronics automation. However, deformable linear object manipulation poses a significant challenge in developing planning and control algorithms, due to the precise and continuous control required to effectively manipulate the deformable ... |
An Evaluation of Action Segmentation Algorithms on Bimanual Manipulation Datasets | https://ieeexplore.ieee.org/document/10341956/ | [
"Andre Meixner",
"Franziska Krebs",
"Noémie Jaquier",
"Tamim Asfour",
"Andre Meixner",
"Franziska Krebs",
"Noémie Jaquier",
"Tamim Asfour"
] | Humans naturally execute many everyday manipulation actions with both arms simultaneously. Similarly, endowing robots with bimanual manipulation task models is key to efficiently perform complex manipulation tasks. To do so, a promising approach is to learn a library of task models from human demonstrations. However, this requires human motions to be meaningfully segmented. In this paper, we propo... |
SoftGPT: Learn Goal-Oriented Soft Object Manipulation Skills by Generative Pre-Trained Heterogeneous Graph Transformer | https://ieeexplore.ieee.org/document/10341846/ | [
"Junjia Liu",
"Zhihao Li",
"Wanyu Lin",
"Sylvain Calinon",
"Kay Chen Tan",
"Fei Chen",
"Junjia Liu",
"Zhihao Li",
"Wanyu Lin",
"Sylvain Calinon",
"Kay Chen Tan",
"Fei Chen"
] | Soft object manipulation tasks in domestic scenes pose a significant challenge for existing robotic skill learning techniques due to their complex dynamics and variable shape characteristics. Since learning new manipulation skills from human demonstration is an effective way for robot applications, developing prior knowledge of the representation and dynamics of soft objects is necessary. In this ... |
Geometric Fault-Tolerant Control of Quadrotors in Case of Rotor Failures: An Attitude Based Comparative Study | https://ieeexplore.ieee.org/document/10341669/ | [
"Jennifer Yeom",
"Guanrui Li",
"Giuseppe Loianno",
"Jennifer Yeom",
"Guanrui Li",
"Giuseppe Loianno"
] | The ability of aerial robots to operate in the presence of failures is crucial in various applications that demand continuous operations, such as surveillance, monitoring, and inspection. In this paper, we propose a fault-tolerant control strategy for quadrotors that can adapt to single and dual complete rotor failures. Our approach augments a classic geometric tracking controller on $S{O}(3)\time... |
UAV-Based Trilateration System for Localization and Tracking of Radio-Tagged Flying Insects: Development and Field Evaluation | https://ieeexplore.ieee.org/document/10341725/ | [
"Jeonghyeon Pak",
"Bosung Kim",
"Chanyoung Ju",
"Sung Hyun You",
"Hyoung Il Son",
"Jeonghyeon Pak",
"Bosung Kim",
"Chanyoung Ju",
"Sung Hyun You",
"Hyoung Il Son"
] | As the interest in ecosystem protection increases, many researchers are focusing on tracking flying insects to preserve biodiversity. Invasive alien species (IAS) such as Vespa velutina nigrithorax require extensive consideration in this regard owing to size and weight limitations. In this paper, we propose and experimentally validate an unmanned aerial vehicle (UAV)-based trilateration system for... |
Canfly: A Can-Sized Autonomous Mini Coaxial Helicopter | https://ieeexplore.ieee.org/document/10341490/ | [
"Neng Pan",
"Rui Jin",
"Chao Xu",
"Fei Gao",
"Neng Pan",
"Rui Jin",
"Chao Xu",
"Fei Gao"
] | The development of autonomous rotary-wing UAVs has shown an evident tendency in miniaturization. However, the side effects brought by miniaturization, such as decreased load capability, shorter flight duration and reduced autonomous ability, seriously hinder its process. In this paper, we first investigate the configurations of different rotary-wing aircraft and optimize the configuration selectio... |
Aerial Manipulator Systems Gain a New Skill: Achieve Contact-based Landing on a Mobile Platform | https://ieeexplore.ieee.org/document/10342395/ | [
"Xiangdong Meng",
"Yuqing He",
"Haoyang Xi",
"Jianda Han",
"Aiguo Song",
"Xiangdong Meng",
"Yuqing He",
"Haoyang Xi",
"Jianda Han",
"Aiguo Song"
] | This paper studies a novel application of an aerial manipulator (AM)-the contact-based landing on a mobile platform. An AM is inherently unstable, under-actuated, and usually loses some DOFs while contacting environments. Meanwhile, the AM's flight state is susceptible to uncertain movements of the mobile platform, such as acceleration, sudden stopping, and reversing. To accomplish the contact-bas... |
AOSoar: Autonomous Orographic Soaring of a Micro Air Vehicle | https://ieeexplore.ieee.org/document/10341699/ | [
"Sunyou Hwang",
"Bart D. W. Remes",
"Guido C. H. E. De Croon",
"Sunyou Hwang",
"Bart D. W. Remes",
"Guido C. H. E. De Croon"
] | Utilizing wind hovering techniques of soaring birds can save energy expenditure and improve the flight endurance of micro air vehicles (MAVs). Here, we present a novel method for fully autonomous orographic soaring without a priori knowledge of the wind field. Specifically, we devise an Incremental Nonlinear Dynamic Inversion (INDI) controller with control allocation, adapting it for autonomous so... |
Error-State Kalman Filter Based External Wrench Estimation for MAVs Under a Cascaded Architecture | https://ieeexplore.ieee.org/document/10342358/ | [
"Yuhan Yin",
"Qingkai Yang",
"Hao Fang",
"Yuhan Yin",
"Qingkai Yang",
"Hao Fang"
] | In many applications such as aerial transportation, delivery, and manipulation, it is essential to know the external wrench exerted on multirotor aerial vehicles precisely. This paper presents an algorithm to estimate external wrench using a rotor speed measurement unit, an inertial measurement unit and a motion capture system. Under a cascaded architecture containing two sub-systems, one error-st... |
Minimally Actuated Tiltrotor for Perching and Normal Force Exertion | https://ieeexplore.ieee.org/document/10341910/ | [
"Dongjae Lee",
"Sunwoo Hwang",
"Changhyeon Kim",
"Seung Jae Lee",
"H. Jin Kim",
"Dongjae Lee",
"Sunwoo Hwang",
"Changhyeon Kim",
"Seung Jae Lee",
"H. Jin Kim"
] | This study presents a new hardware design and control of a minimally actuated 5 control degrees of freedom (CDoF) quadrotor-based tiltrotor. The proposed tiltrotor possesses several characteristics distinct from those found in existing works, including: 1) minimal number of actuators for 5 CDoF, 2) large margin to generate interaction force during aerial physical interaction (APhI), and 3) no mech... |
Nonlinear Model Predictive Control for Cooperative Transportation and Manipulation of Cable Suspended Payloads with Multiple Quadrotors | https://ieeexplore.ieee.org/document/10341785/ | [
"Guanrui Li",
"Giuseppe Loianno",
"Guanrui Li",
"Giuseppe Loianno"
] | Autonomous Micro Aerial Vehicles (MAVs) such as quadrotors equipped with manipulation mechanisms have the potential to assist humans in tasks such as construction and package delivery. Cables are a promising option for manipulation mechanisms due to their low weight, low cost, and simple design. However, designing control and planning strategies for cable mechanisms presents challenges due to indi... |
Image-Based Visual Servo Control for Aerial Manipulation Using a Fully-Actuated UAV | https://ieeexplore.ieee.org/document/10342145/ | [
"Guanqi He",
"Yash Jangir",
"Junyi Geng",
"Mohammadreza Mousaei",
"Dongwei Bai",
"Sebastian Scherer",
"Guanqi He",
"Yash Jangir",
"Junyi Geng",
"Mohammadreza Mousaei",
"Dongwei Bai",
"Sebastian Scherer"
] | Using Unmanned Aerial Vehicles (UAVs) to per-form high-altitude manipulation tasks beyond just passive visual application can reduce the time, cost, and risk of human workers. Prior research on aerial manipulation has relied on either ground truth state estimate or GPS/total station with some Simultaneous Localization and Mapping (SLAM) algorithms, which may not be practical for many applications ... |
DroNeRF: Real-Time Multi-Agent Drone Pose Optimization for Computing Neural Radiance Fields | https://ieeexplore.ieee.org/document/10342420/ | [
"Dipam Patel",
"Phu Pham",
"Aniket Bera",
"Dipam Patel",
"Phu Pham",
"Aniket Bera"
] | We present a novel optimization algorithm called DroNeRF for the autonomous positioning of monocular camera drones around an object for real-time 3D reconstruction using only a few images. Neural Radiance Fields, or NeRF, is a novel view synthesis technique used to generate new views of an object or scene from a set of input images. Using drones in conjunction with NeRF provides a unique and dynam... |
Generation of Time-Varying Impedance Attacks Against Haptic Shared Control Steering Systems | https://ieeexplore.ieee.org/document/10342459/ | [
"Alireza Mohammadi",
"Hafiz Malik",
"Alireza Mohammadi",
"Hafiz Malik"
] | The safety-critical nature of vehicle steering is one of the main motivations for exploring the space of possible cyber-physical attacks against the steering systems of modern vehicles. This paper investigates the adversarial capabilities for destabilizing the interaction dynamics between human drivers and vehicle haptic shared control (HSC) steering systems. In contrast to the conventional roboti... |
Haptic Dataset Augmentation with Subjective QoE Labels using Conditional Generative Adversarial Network | https://ieeexplore.ieee.org/document/10341967/ | [
"Zican Wang",
"Xiao Xu",
"Dong Yang",
"Zhenyu Wang",
"Sarah Shtaierman",
"Eckehard Steinbach",
"Zican Wang",
"Xiao Xu",
"Dong Yang",
"Zhenyu Wang",
"Sarah Shtaierman",
"Eckehard Steinbach"
] | This paper proposes a novel Generative Adversarial Network (GAN)-based strategy to augment subjective haptic Quality of Experience (QoE) datasets for bilateral teleoperation with haptic feedback without conducting time-consuming subjective experiments. In our previous work, we proposed a multi-assessment fusion approach to predict subjective haptic quality using a collection of objective metrics. ... |
A Physically Based Deformable Model with Haptic Feedback for Real-Time Robotic Surgery Simulation | https://ieeexplore.ieee.org/document/10341694/ | [
"Saul Heredia",
"Hiromasa Masuda",
"Atsushi Miyamoto",
"Yohei Kuroda",
"Saul Heredia",
"Hiromasa Masuda",
"Atsushi Miyamoto",
"Yohei Kuroda"
] | Surgical simulators have been under development for years, formerly intended for surgical training and recently applied for training machine learning models. These systems often employ computationally efficient methods such as mass-spring models or position-based dynamics that prioritize real-time execution over physical accuracy, while the use of the finite element method (FEM) has been limited d... |
Learning Contact-Based State Estimation for Assembly Tasks | https://ieeexplore.ieee.org/document/10342219/ | [
"Johannes Pankert",
"Marco Hutter",
"Johannes Pankert",
"Marco Hutter"
] | Robotic object manipulation requires knowledge of the environment's state. In particular, the object poses of fixed elements in the environment relative to the robot and the in-hand poses of grasped objects are of interest. For insertion tasks with tight tolerances, the accuracy of vision systems to estimate the object and in-hand pose is not high enough. This work proposes a state estimation syst... |
Evaluation of a 7-DoFs Robotic Manipulator as Haptic Interface During Planar Reaching Tasks | https://ieeexplore.ieee.org/document/10342470/ | [
"Alessia Noccaro",
"Silvia Buscaglione",
"Mattia Pinardi",
"Giovanni Di Pino",
"Domenico Formica",
"Alessia Noccaro",
"Silvia Buscaglione",
"Mattia Pinardi",
"Giovanni Di Pino",
"Domenico Formica"
] | In this work, we evaluated the suitability of using a 7 degrees of freedom robotic manipulator as a planar haptic interface for studies in motor neuroscience. In particular, we assessed to what extent it can measure human movement and forces without applying undesired perturbations. To this aim, we evaluated the amount of perturbation exerted by the robot during planar reaching movements when cont... |
Soft, Modular, Shape-Changing Displays with Hyperelastic Bubble Arrays | https://ieeexplore.ieee.org/document/10341591/ | [
"Matthew R. Devlin",
"Tianshu Liu",
"Mengjia Zhu",
"Nathan S. Usevitch",
"Nicholas Colonnese",
"Amirhossein H. Memar",
"Matthew R. Devlin",
"Tianshu Liu",
"Mengjia Zhu",
"Nathan S. Usevitch",
"Nicholas Colonnese",
"Amirhossein H. Memar"
] | Incorporating compliance into shape-changing displays can improve their wearability and actuation modalities. While recent advances in soft actuators highlight promising paths for soft shape-changing displays, these displays currently face some practical challenges of device failure and limited actuator displacement. A monolithic fabrication processes means the device is challenging to repair, for... |
Soft Optical Sensor and Haptic Feedback System for Remote and Robot-Assisted Palpation | https://ieeexplore.ieee.org/document/10341754/ | [
"Arincheyan Gerald",
"Jonathan Ye",
"Rukaiya Batliwala",
"Patra Hsu",
"Johann Pang",
"Sheila Russo",
"Arincheyan Gerald",
"Jonathan Ye",
"Rukaiya Batliwala",
"Patra Hsu",
"Johann Pang",
"Sheila Russo"
] | Robotic palpation shows significant potential to improve the accuracy and speed of tumor identification. How-ever, robotic palpation mechanisms often lack haptic feedback, making it difficult for the surgeon to identify variations in tissue stiffness. This paper presents a soft optical sensor integrated with a wearable haptic glove for tumor detection during robotic palpation. The sensor contains ... |
TIMS: A Tactile Internet-Based Micromanipulation System with Haptic Guidance for Surgical Training | https://ieeexplore.ieee.org/document/10341980/ | [
"Jialin Lin",
"Xiaoqing Guo",
"Wen Fan",
"Wei Li",
"Yuanyi Wang",
"Jiaming Liang",
"Jindong Liu",
"Weiru Liu",
"Lei Wei",
"Dandan Zhang",
"Jialin Lin",
"Xiaoqing Guo",
"Wen Fan",
"Wei Li",
"Yuanyi Wang",
"Jiaming Liang",
"Jindong Liu",
"Weiru Liu",
"Lei Wei",
"Dandan Zhang"
] | Microsurgery involves the dexterous manipulation of delicate tissue or fragile structures, such as small blood vessels and nerves, under a microscope. To address the limitations of imprecise manipulation of human hands, robotic systems have been developed to assist surgeons in performing complex microsurgical tasks with greater precision and safety. However, the steep learning curve for robot-assi... |
A Teleoperated MR-Safe Haptic System for Magnetic Resonance Imaging-Guided Prostate Needle Biopsies | https://ieeexplore.ieee.org/document/10342113/ | [
"Evelyn Mendoza",
"John P. Whitney",
"Evelyn Mendoza",
"John P. Whitney"
] | Real-time magnetic resonance imaging (MRI) in-terventions are significantly impacted by material compatibility problems and size constraints in the MRI bore. Limited physi-cian access to patients within the bore of the MRI necessitates iterative positioning and imaging, which prolongs the duration of the procedure and increases patient risk. We present a passive MR-safe haptic teleoperation device... |
Symmetry-Based Modeling and Hybrid Orientation-Force Control of Wearable Cutaneous Haptic Device | https://ieeexplore.ieee.org/document/10341859/ | [
"Somang Lee",
"Hyunsu Kim",
"Dongjun Lee",
"Somang Lee",
"Hyunsu Kim",
"Dongjun Lee"
] | We propose novel symmetry-based modeling and hybrid orientation-force control frameworks for cutaneous haptic device (CHD) to generate precise three degree-of-freedom (DoF) contact force on the fingertip robustly against user variability. The CHD hardware is designed in a form of an underactuated cable-driven parallel mechanism, with springs placed along the tendon to stabilize the pose. We analyz... |
Learning-Augmented Model-Based Planning for Visual Exploration | https://ieeexplore.ieee.org/document/10341773/ | [
"Yimeng Li",
"Arnab Debnath",
"Gregory J. Stein",
"Jana Košecká",
"Yimeng Li",
"Arnab Debnath",
"Gregory J. Stein",
"Jana Košecká"
] | We consider the problem of time-limited robotic exploration in previously unseen environments where exploration is limited by a predefined amount of time. We propose a novel exploration approach using learning-augmented model-based planning. We generate a set of sub goals associated with frontiers on the current map and derive a Bellman Equation for exploration with these subgoals. Visual sensing ... |
DMCL: Robot Autonomous Navigation via Depth Image Masked Contrastive Learning | https://ieeexplore.ieee.org/document/10341836/ | [
"Jiahao Jiang",
"Ping Li",
"Xudong Lv",
"Yuxiang Yang",
"Jiahao Jiang",
"Ping Li",
"Xudong Lv",
"Yuxiang Yang"
] | Achieving high performance in deep reinforcement learning relies heavily on the ability to obtain good state representations from pixel inputs. However, learning an observation-space-to-action-space mapping from high-dimensional inputs is challenging in reinforcement learning, particularly when dealing with consecutive depth images as input states. In addition, we observe that the consecutive inpu... |
Image-based Regularization for Action Smoothness in Autonomous Miniature Racing Car with Deep Reinforcement Learning | https://ieeexplore.ieee.org/document/10342029/ | [
"Hoang-Giang Cao",
"I Lee",
"Bo-Jiun Hsu",
"Zheng- Yi Lee",
"Yu-Wei Shih",
"Hsueh-Cheng Wang",
"I-Chen Wu",
"Hoang-Giang Cao",
"I Lee",
"Bo-Jiun Hsu",
"Zheng- Yi Lee",
"Yu-Wei Shih",
"Hsueh-Cheng Wang",
"I-Chen Wu"
] | Deep reinforcement learning has achieved signif-icant results in low-level controlling tasks. However, for some applications like autonomous driving and drone flying, it is difficult to control behavior stably since the agent may suddenly change its actions which often lowers the controlling sys-tem's efficiency, induces excessive mechanical wear, and causes uncontrollable, dangerous behavior to t... |
UnLoc: A Universal Localization Method for Autonomous Vehicles using LiDAR, Radar and/or Camera Input | https://ieeexplore.ieee.org/document/10342046/ | [
"Muhammad Ibrahim",
"Naveed Akhtar",
"Saeed Anwar",
"Ajmal Mian",
"Muhammad Ibrahim",
"Naveed Akhtar",
"Saeed Anwar",
"Ajmal Mian"
] | Localization is a fundamental task in robotics for autonomous navigation. Existing localization methods rely on a single input data modality or train several computational models to process different modalities. This leads to stringent computational requirements and sub-optimal results that fail to capitalize on the complementary information in other data streams. This paper proposes UnLoc, a nove... |
A Complementarity-Based Switch-Fuse System for Improved Visual Place Recognition | https://ieeexplore.ieee.org/document/10341876/ | [
"Maria Waheed",
"Sania Waheed",
"Michael Milford",
"Klaus McDonald-Maier",
"Shoaib Ehsan",
"Maria Waheed",
"Sania Waheed",
"Michael Milford",
"Klaus McDonald-Maier",
"Shoaib Ehsan"
] | Recently several fusion and switching based approaches have been presented to solve the problem of Visual Place Recognition. In spite of these systems demonstrating significant boost in VPR performance they each have their own set of limitations. The multi-process fusion systems usually involve employing brute force and running all available VPR techniques simultaneously while the switching method... |
RREx-BoT: Remote Referring Expressions with a Bag of Tricks | https://ieeexplore.ieee.org/document/10342093/ | [
"Gunnar A. Sigurdsson",
"Jesse Thomason",
"Gaurav S. Sukhatme",
"Robinson Piramuthu",
"Gunnar A. Sigurdsson",
"Jesse Thomason",
"Gaurav S. Sukhatme",
"Robinson Piramuthu"
] | Household robots operate in the same space for years. Such robots incrementally build dynamic maps that can be used for tasks requiring remote object localization. However, benchmarks in robot learning often test generalization through inference on tasks in unobserved environments. In an observed environment, locating an object is reduced to choosing from among all object proposals in the environm... |
PLPL-VIO: A Novel Probabilistic Line Measurement Model for Point-Line-Based Visual-Inertial Odometry | https://ieeexplore.ieee.org/document/10342387/ | [
"Zewen Xu",
"Hao Wei",
"Fulin Tang",
"Yidi Zhang",
"Yihong Wu",
"Gang Ma",
"Shuzhe Wu",
"Xin Jin",
"Zewen Xu",
"Hao Wei",
"Fulin Tang",
"Yidi Zhang",
"Yihong Wu",
"Gang Ma",
"Shuzhe Wu",
"Xin Jin"
] | Point and line features are complementary in Visual-Inertial Odometry (VIO) or Visual-Inertial Simultaneous Localization And Mapping (VI-SLAM) systems. The advantage of combining these two types of features relies on their proper weighting in the cost function, usually set by their uncertainty. Compared with point features, setting line segment endpoints' uncertainty with isotropic distribution is... |
Multi-Goal Audio-Visual Navigation Using Sound Direction Map | https://ieeexplore.ieee.org/document/10341819/ | [
"Haru Kondoh",
"Asako Kanezaki",
"Haru Kondoh",
"Asako Kanezaki"
] | Over the past few years, there has been a great deal of research on navigation tasks in indoor environments using deep reinforcement learning agents. Most of these tasks use only visual information in the form of first-person images to navigate to a single goal. More recently, tasks that simultaneously use visual and auditory information to navigate to the sound source and even navigation tasks wi... |
Directed Real-World Learned Exploration | https://ieeexplore.ieee.org/document/10341504/ | [
"Matthias Hutsebaut-Buysse",
"Ferran Gebelli Guinjoan",
"Erwin Rademakers",
"Steven Latré",
"Abdellatif Bey Temsamani",
"Kevin Mets",
"Erik Mannens",
"Tom De Schepper",
"Matthias Hutsebaut-Buysse",
"Ferran Gebelli Guinjoan",
"Erwin Rademakers",
"Steven Latré",
"Abdellatif Bey Temsamani",
"Kevin Mets",
"Erik Mannens",
"Tom De Schepper"
] | Automated Guided Vehicles (AGV) are omnipresent, and are able to carry out various kind of preprogrammed tasks. Unfortunately, a lot of manual configuration is still required in order to make these systems operational, and configuration needs to be re-done when the environment or task is changed. As an alternative to current inflexible methods, we employ a learning based method in order to perform... |
Learning Whom to Trust in Navigation: Dynamically Switching Between Classical and Neural Planning | https://ieeexplore.ieee.org/document/10342308/ | [
"Sombit Dey",
"Assem Sadek",
"Gianluca Monaci",
"Boris Chidlovskii",
"Christian Wolf",
"Sombit Dey",
"Assem Sadek",
"Gianluca Monaci",
"Boris Chidlovskii",
"Christian Wolf"
] | Navigation of terrestrial robots is typically addressed either with localization and mapping (SLAM) followed by classical planning on the dynamically created maps, or by machine learning (ML), often through end-to-end training with reinforcement learning (RL) or imitation learning (IL). Recently, modular designs have achieved promising results, and hybrid algorithms that combine ML with classical ... |
Learning Deep Sensorimotor Policies for Vision-Based Autonomous Drone Racing | https://ieeexplore.ieee.org/document/10341805/ | [
"Jiawei Fu",
"Yunlong Song",
"Yan Wu",
"Fisher Yu",
"Davide Scaramuzza",
"Jiawei Fu",
"Yunlong Song",
"Yan Wu",
"Fisher Yu",
"Davide Scaramuzza"
] | The development of effective vision-based algorithms has been a significant challenge in achieving autonomous drones, which promise to offer immense potential for many real-world applications. This paper investigates learning deep sensorimotor policies for vision-based drone racing, which is a particularly demanding setting for testing the limits of an algorithm. Our method combines feature repres... |
Magnetic Navigation Using Attitude-Invariant Magnetic Field Information for Loop Closure Detection | https://ieeexplore.ieee.org/document/10342466/ | [
"Natalia Pavlasek",
"Charles Champagne Cossette",
"David Roy-Guay",
"James Richard Forbes",
"Natalia Pavlasek",
"Charles Champagne Cossette",
"David Roy-Guay",
"James Richard Forbes"
] | Indoor magnetic fields are a combination of Earth's magnetic field and disruptions induced by ferromag-netic objects, such as steel structural components in buildings. As a result of these disruptions, pervasive in indoor spaces, mag-netic field data is often omitted from navigation algorithms in indoor environments. This paper leverages the spatially-varying disruptions to Earth's magnetic field ... |
Locking On: Leveraging Dynamic Vehicle-Imposed Motion Constraints to Improve Visual Localization | https://ieeexplore.ieee.org/document/10341635/ | [
"Stephen Hausler",
"Sourav Garg",
"Punarjay Chakravarty",
"Shubham Shrivastava",
"Ankit Vora",
"Michael Milford",
"Stephen Hausler",
"Sourav Garg",
"Punarjay Chakravarty",
"Shubham Shrivastava",
"Ankit Vora",
"Michael Milford"
] | Most 6-DoF localization and SLAM systems use static landmarks but ignore dynamic objects because they cannot be usefully incorporated into a typical pipeline. Where dynamic objects have been incorporated, typical approaches have attempted relatively sophisticated identification and localization of these objects, limiting their robustness or general utility. In this research, we propose a middle gr... |
Uncertainty-Aware Gaussian Mixture Model for UWB Time Difference of Arrival Localization in Cluttered Environments | https://ieeexplore.ieee.org/document/10342365/ | [
"Wenda Zhao",
"Abhishek Goudar",
"Mingliang Tang",
"Xinyuan Qiao",
"Angela P. Schoellig",
"Wenda Zhao",
"Abhishek Goudar",
"Mingliang Tang",
"Xinyuan Qiao",
"Angela P. Schoellig"
] | Ultra-wideband (UWB) time difference of arrival (TDOA)-based localization has emerged as a low-cost and scalable indoor positioning solution. However, in cluttered environments, the performance of UWB TDOA-based localization deteriorates due to the biased and non-Gaussian noise distributions induced by obstacles. In this work, we present a bi-level optimization-based joint localization and noise m... |
CREPES: Cooperative RElative Pose Estimation System | https://ieeexplore.ieee.org/document/10342523/ | [
"Zhiren Xun",
"Jian Huang",
"Zhehan Li",
"Zhenjun Ying",
"Yingjian Wang",
"Chao Xu",
"Fei Gao",
"Yanjun Cao",
"Zhiren Xun",
"Jian Huang",
"Zhehan Li",
"Zhenjun Ying",
"Yingjian Wang",
"Chao Xu",
"Fei Gao",
"Yanjun Cao"
] | Mutual localization plays a crucial role in multi-robot cooperation. CREPES, a novel system that focuses on six degrees of freedom (DOF) relative pose estimation for multi-robot systems, is proposed in this paper. CREPES has a compact hardware design using active infrared (IR) LEDs, an IR fish-eye camera, an ultra-wideband (UWB) module and an inertial measurement unit (IMU). By leveraging IR light... |
navlie: A Python Package for State Estimation on Lie Groups | https://ieeexplore.ieee.org/document/10342362/ | [
"Charles Champagne Cossette",
"Mitchell Cohen",
"Vassili Korotkine",
"Arturo Del Castillo Bernal",
"Mohammed Ayman Shalaby",
"James Richard Forbes",
"Charles Champagne Cossette",
"Mitchell Cohen",
"Vassili Korotkine",
"Arturo Del Castillo Bernal",
"Mohammed Ayman Shalaby",
"James Richard Forbes"
] | The ability to rapidly test a variety of algorithms for an arbitrary state estimation task is valuable in the prototyping phase of navigation systems. Lie group theory is now mainstream in the robotics community, and hence estimation prototyping tools should allow state definitions that belong to manifolds. A new package, called navlie, provides a framework that allows a user to model a large clas... |
A Relative Infrastructure-less Localization Algorithm for Decentralized and Autonomous Swarm Formation | https://ieeexplore.ieee.org/document/10342168/ | [
"Dominik Schindler",
"Vlad Niculescu",
"Tommaso Polonelli",
"Daniele Palossi",
"Luca Benini",
"Michele Magno",
"Dominik Schindler",
"Vlad Niculescu",
"Tommaso Polonelli",
"Daniele Palossi",
"Luca Benini",
"Michele Magno"
] | Decentralized and autonomous control of Unmanned Aerial Vehicle (UAV) swarms is a key enabler for cooperative systems and infrastructure-less formation flights. However, UAVs often lack reliable heading angle measurements, especially in indoor scenarios, space, and GNSS-denied environments, posing an additional observability challenge on range-based relative localization. We tackle this problem by... |
RaSpectLoc: RAman SPECTroscopy-dependent robot LOCalisation | https://ieeexplore.ieee.org/document/10342198/ | [
"Christopher Thirgood",
"Oscar Mendez",
"Erin Chao Ling",
"Jon Storey",
"Simon Hadfield",
"Christopher Thirgood",
"Oscar Mendez",
"Erin Chao Ling",
"Jon Storey",
"Simon Hadfield"
] | This paper presents a new information source for supporting robot localisation: material composition. The proposed method complements the existing visual, structural, and semantic cues utilized in the literature. However, it has a distinct advantage in its ability to differentiate structurally [23], visually [25] or categorically [1] similar objects such as different doors, by using Raman spectrom... |
Need for Speed: Fast Correspondence-Free Lidar-Inertial Odometry Using Doppler Velocity | https://ieeexplore.ieee.org/document/10341596/ | [
"David J. Yoon",
"Keenan Burnett",
"Johann Laconte",
"Yi Chen",
"Heethesh Vhavle",
"Soeren Kammel",
"James Reuther",
"Timothy D. Barfoot",
"David J. Yoon",
"Keenan Burnett",
"Johann Laconte",
"Yi Chen",
"Heethesh Vhavle",
"Soeren Kammel",
"James Reuther",
"Timothy D. Barfoot"
] | In this paper, we present a fast, lightweight odometry method that uses the Doppler velocity measurements from a Frequency-Modulated Continuous-Wave (FMCW) lidar without data association. FMCW lidar is a recently emerging technology that enables per-return relative radial velocity measurements via the Doppler effect. Since the Doppler measurement model is linear with respect to the 6-degrees-of-fr... |
Uncertainty Analysis for Accurate Ground Truth Trajectories with Robotic Total Stations | https://ieeexplore.ieee.org/document/10341529/ | [
"Maxime Vaidis",
"William Dubois",
"Effie Daum",
"Damien LaRocque",
"François Pomerleau",
"Maxime Vaidis",
"William Dubois",
"Effie Daum",
"Damien LaRocque",
"François Pomerleau"
] | In the context of robotics, accurate ground truth positioning is essential for the development of Simultaneous Localization and Mapping (SLAM) and control algorithms. Robotic Total Stations (RTSs) provide accurate and precise reference positions in different types of outdoor environments, especially when compared to the limited accuracy of Global Navigation Satellite System (GNSS) in cluttered are... |
Graph Matching Optimization Network for Point Cloud Registration | https://ieeexplore.ieee.org/document/10342346/ | [
"Qianliang Wu",
"Yaqi Shen",
"Haobo Jiang",
"Guofeng Mei",
"Yaqing Ding",
"Lei Luo",
"Jin Xie",
"Jian Yang",
"Qianliang Wu",
"Yaqi Shen",
"Haobo Jiang",
"Guofeng Mei",
"Yaqing Ding",
"Lei Luo",
"Jin Xie",
"Jian Yang"
] | Point Cloud Registration is a fundamental and challenging problem in 3D computer vision. Recent works often utilize geometric structure features in downsampled points (patches) to seek correspondences, then propagate these sparse patch correspondences to the dense level in the corresponding patches' neighborhood. However, they neglect the explicit global scale rigid constraint at the dense level p... |
SEAL: Simultaneous Exploration and Localization for Multi-Robot Systems | https://ieeexplore.ieee.org/document/10342157/ | [
"Ehsan Latif",
"Ramviyas Parasuraman",
"Ehsan Latif",
"Ramviyas Parasuraman"
] | The availability of accurate localization is critical for multi-robot exploration strategies; noisy or inconsistent localization causes failure in meeting exploration objectives. We aim to achieve high localization accuracy with contemporary exploration map belief and vice versa without needing global localization information. This paper proposes a novel simultaneous exploration and localization (... |
Discrete-Time Adaptive Control Algorithm for Coordination of Multiagent Systems in the Presence of Coupled Dynamics | https://ieeexplore.ieee.org/document/10341404/ | [
"Islam A. Aly",
"K. Merve Dogan",
"Islam A. Aly",
"K. Merve Dogan"
] | Discrete-time architectures have an advantage over their continuous counterparts as they can be directly executed on embedded hardware without the need for dis-cretization, and discretization can result in a loss of stability margin. This paper presents a discrete-time adaptive control architecture for uncertain scalar multi agent systems with coupled dynamics. Our strategy includes observer dynam... |
Risk-Tolerant Task Allocation and Scheduling in Heterogeneous Multi-Robot Teams | https://ieeexplore.ieee.org/document/10341837/ | [
"Jinwoo Park",
"Andrew Messing",
"Harish Ravichandar",
"Seth Hutchinson",
"Jinwoo Park",
"Andrew Messing",
"Harish Ravichandar",
"Seth Hutchinson"
] | Effective coordination of heterogeneous multi-robot teams requires optimizing allocations, schedules, and motion plans in order to satisfy complex multi-dimensional task requirements. This challenge is exacerbated by the fact that real-world applications inevitably introduce uncertainties into robot capabilities and task requirements. In this paper, we extend our previous work on trait-based time-... |
PuSHR: A Multirobot System for Nonprehensile Rearrangement | https://ieeexplore.ieee.org/document/10341853/ | [
"Sidharth Talia",
"Arnav Thareja",
"Christoforos Mavrogiannis",
"Matt Schmittle",
"Siddhartha S. Srinivasa",
"Sidharth Talia",
"Arnav Thareja",
"Christoforos Mavrogiannis",
"Matt Schmittle",
"Siddhartha S. Srinivasa"
] | We focus on the problem of rearranging a set of objects with a team of car-like robot pushers built using off-the-shelf components. Maintaining control of pushed objects while avoiding collisions in a tight space demands highly coordinated motion that is challenging to execute on constrained hardware. Centralized replanning approaches become intractable even for small-sized problems whereas decent... |
Game-Theoretical Approach to Multi-Robot Task Allocation Using a Bio-Inspired Optimization Strategy | https://ieeexplore.ieee.org/document/10341947/ | [
"Shengkang Chen",
"Tony X. Lin",
"Fumin Zhang",
"Shengkang Chen",
"Tony X. Lin",
"Fumin Zhang"
] | This paper introduces a game-theoretical approach to the multi-robot task allocation problem, where each robot is considered as self-interested and cannot share its personal utility functions. We consider the case where each robot can execute multiple tasks and each task requires only one robot. For real-world applications with mobile robots, we design a utility function that includes both assignm... |
Multi-Robot Planning on Dynamic Topological Graphs Using Mixed- Integer Programming | https://ieeexplore.ieee.org/document/10341497/ | [
"Cora A. Dimmig",
"Kevin C. Wolfe",
"Joseph Moore",
"Cora A. Dimmig",
"Kevin C. Wolfe",
"Joseph Moore"
] | Planning for multi-robot teams in complex environments is a challenging problem, especially when these teams must coordinate to accomplish a common objective. In general, optimal solutions to these planning problems are computationally intractable, since the decision space grows exponentially with the number of robots. In this paper, we present a novel approach for multi-robot planning on topologi... |
Heterogeneous Coalition Formation and Scheduling with Multi-Skilled Robots | https://ieeexplore.ieee.org/document/10342489/ | [
"Ashay Aswale",
"Carlo Pinciroli",
"Ashay Aswale",
"Carlo Pinciroli"
] | We present an approach to task scheduling in heterogeneous multi-robot systems. In our setting, the tasks to complete require diverse skills. We assume that each robot is multi-skilled, i.e., each robot offers a subset of the possible skills. This makes the formation of heterogeneous teams (coalitions) a requirement for task completion. We present two centralized algorithms to schedule robots acro... |
Measuring Human-Robot Team Benefits Under Time Pressure in a Virtual Reality Testbed | https://ieeexplore.ieee.org/document/10341794/ | [
"Katarina Popović",
"Millicent Schlafly",
"Ahalya Prabhakar",
"Christopher Kim",
"Todd D. Murphey",
"Katarina Popović",
"Millicent Schlafly",
"Ahalya Prabhakar",
"Christopher Kim",
"Todd D. Murphey"
] | During a natural disaster such as hurricane, earthquake, or fire, robots have the potential to explore vast areas and provide valuable aid in search & rescue efforts. These scenarios are often high-pressure and time-critical with dynamically-changing task goals. One limitation to these large scale deployments is effective human-robot interaction. Prior work shows that collaboration between one hum... |
Robust Electric Vehicle Balancing of Autonomous Mobility-on-Demand System: A Multi-Agent Reinforcement Learning Approach | https://ieeexplore.ieee.org/document/10342263/ | [
"Sihong He",
"Shuo Han",
"Fei Miao",
"Sihong He",
"Shuo Han",
"Fei Miao"
] | Electric autonomous vehicles (EAVs) are getting attention in future autonomous mobility-on-demand (AMoD) systems due to their economic and societal benefits. However, EAVs' unique charging patterns (long charging time, high charging frequency, unpredictable charging behaviors, etc.) make it challenging to accurately predict the EAVs supply in E-AMoD systems. Furthermore, the mobility demand's pred... |
Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained Environments | https://ieeexplore.ieee.org/document/10342203/ | [
"Calvin Tanama",
"Kunyu Peng",
"Zdravko Marinov",
"Rainer Stiefelhagen",
"Alina Roitberg",
"Calvin Tanama",
"Kunyu Peng",
"Zdravko Marinov",
"Rainer Stiefelhagen",
"Alina Roitberg"
] | Deep learning-based models are at the top of most driver observation benchmarks due to their remarkable accuracies but come with a high computational cost, while the resources are often limited in real-world driving scenarios. This paper presents a lightweight framework for resource- efficient driver activity recognition. We enhance 3D MobileNet, a speed-optimized neural architecture for video cla... |
Joint Out-of-Distribution Detection and Uncertainty Estimation for Trajectory Prediction | https://ieeexplore.ieee.org/document/10341616/ | [
"Julian Wiederer",
"Julian Schmidt",
"Ulrich Kressel",
"Klaus Dietmayer",
"Vasileios Belagiannis",
"Julian Wiederer",
"Julian Schmidt",
"Ulrich Kressel",
"Klaus Dietmayer",
"Vasileios Belagiannis"
] | Despite the significant research efforts on trajectory prediction for automated driving, limited work exists on assessing the prediction reliability. To address this limitation we propose an approach that covers two sources of error, namely novel situations with out-of-distribution (OOD) detection and the complexity in in-distribution (ID) situations with uncertainty estimation. We introduce two m... |
Deep Reinforcement Learning-Based Intelligent Traffic Signal Controls with Optimized CO2 Emissions | https://ieeexplore.ieee.org/document/10341972/ | [
"Pedram Agand",
"Alexey Iskrov",
"Mo Chen",
"Pedram Agand",
"Alexey Iskrov",
"Mo Chen"
] | Nowadays, transportation networks face the challenge of sub-optimal control policies that can have adverse effects on human health, the environment, and contribute to traffic congestion. Increased levels of air pollution and extended commute times caused by traffic bottlenecks make intersection traffic signal controllers a crucial component of modern transportation infrastructure. Despite several ... |
Hierarchical Attention Network for Planning-Informed Multi-Agent Trajectory Prediction | https://ieeexplore.ieee.org/document/10341557/ | [
"Wenyi Xiong",
"Jian Chen",
"Xinfang Zhang",
"Qi Wang",
"Ziheng Qi",
"Wenyi Xiong",
"Jian Chen",
"Xinfang Zhang",
"Qi Wang",
"Ziheng Qi"
] | The accurate prediction of the neighboring vehicles' trajectories affects the security of autonomous driving vehicles. However, it is challenging for existing methods to anticipating the trajectories of vehicles in the vicinity due to the uncertainty of driving behaviors and the complex interaction patterns of traffic flows. In this study, incorporating the planning information of the ego vehicle,... |
A Two-Stage Based Social Preference Recognition in Multi-Agent Autonomous Driving System | https://ieeexplore.ieee.org/document/10341803/ | [
"Jintao Xue",
"Dongkun Zhang",
"Rong Xiong",
"Yue Wang",
"Eryun Liu",
"Jintao Xue",
"Dongkun Zhang",
"Rong Xiong",
"Yue Wang",
"Eryun Liu"
] | Multi-Agent Reinforcement Learning (MARL) has become a promising solution for constructing a multi-agent autonomous driving system (MADS) in complex and dense scenarios. But most methods consider agents acting selfishly, which leads to conflict behaviors. Some existing works incorporate the concept of social value orientation (SVO) to promote coordination, but they lack the knowledge of other agen... |
RLPG: Reinforcement Learning Approach for Dynamic Intra-Platoon Gap Adaptation for Highway On-Ramp Merging | https://ieeexplore.ieee.org/document/10341918/ | [
"Sushma Reddy Yadavalli",
"Lokesh Chandra Das",
"Myounggyu Won",
"Sushma Reddy Yadavalli",
"Lokesh Chandra Das",
"Myounggyu Won"
] | A platoon refers to a group of vehicles traveling together in very close proximity using automated driving technology. Owing to its immense capacity to improve fuel efficiency, driving safety, and driver comfort, platooning technology has garnered substantial attention from the autonomous vehicle research community. Although highly advantageous, recent research has uncovered that an excessively sm... |
P4P: Conflict-Aware Motion Prediction for Planning in Autonomous Driving | https://ieeexplore.ieee.org/document/10342247/ | [
"Qiao Sun",
"Xin Huang",
"Brian C. Williams",
"Hang Zhao",
"Qiao Sun",
"Xin Huang",
"Brian C. Williams",
"Hang Zhao"
] | Motion prediction is crucial in enabling safe motion planning for autonomous vehicles in interactive scenarios. It allows the planner to identify potential conflicts with other traffic agents and generate safe plans. Existing motion predictors often focus on reducing prediction errors, yet it remains an open question on how well they help identify conflicts for the planner, which are critical to t... |
A Thousand Worlds: Scenery Specification and Generation for Simulation-Based Testing of Mobile Robot Navigation Stacks | https://ieeexplore.ieee.org/document/10342315/ | [
"Samuel Parra",
"Argentina Ortega",
"Sven Schneider",
"Nico Hochgeschwender",
"Samuel Parra",
"Argentina Ortega",
"Sven Schneider",
"Nico Hochgeschwender"
] | Is mobile robot navigation a solved problem? We asked this question to 14 professional robot software engineers who work with navigation stacks of mobile, wheeled robots on a daily basis. They unanimously report that it remains challenging to ensure the performance of their mobile robots. We find that the method of choice to verify a robot's performance is to expose it to different environments un... |
RAIST: Learning Risk Aware Traffic Interactions via Spatio-Temporal Graph Convolutional Networks | https://ieeexplore.ieee.org/document/10341578/ | [
"Videsh Suman",
"Phu Pham",
"Aniket Bera",
"Videsh Suman",
"Phu Pham",
"Aniket Bera"
] | A key aspect of driving a road vehicle is to interact with other road users, assess their intentions and make riskaware tactical decisions. An intuitive approach to enabling an intelligent automated driving system would be incorporating some aspects of human driving behavior. To this end, we propose a novel driving framework for egocentric views based on spatio-temporal traffic graphs. The traffic... |
Look Before You Drive: Boosting Trajectory Forecasting via Imagining Future | https://ieeexplore.ieee.org/document/10341509/ | [
"Yixuan Fan",
"Xin Liu",
"Yali Li",
"Shengjin Wang",
"Yixuan Fan",
"Xin Liu",
"Yali Li",
"Shengjin Wang"
] | Predicting the future trajectories of other agents in the scene fast and effectively is crucial for autonomous driving systems. We note that high-quality predictions require us to take into account the subjective initiative of the target agents, which is reflected by the fact that they themselves make decisions based on their own predictions about the future, just like our ego vehicle's prediction... |
Leveraging Cloud Computing to Make Autonomous Vehicles Safer | https://ieeexplore.ieee.org/document/10341821/ | [
"Peter Schafhalter",
"Sukrit Kalra",
"Le Xu",
"Joseph E. Gonzalez",
"Ion Stoica",
"Peter Schafhalter",
"Sukrit Kalra",
"Le Xu",
"Joseph E. Gonzalez",
"Ion Stoica"
] | The safety of autonomous vehicles (AVs) depends on their ability to perform complex computations on high-volume sensor data in a timely manner. Their ability to run these computations with state-of-the-art models is limited by the processing power and slow update cycles of their onboard hardware. In contrast, cloud computing offers the ability to burst computation to vast amounts of the latest gen... |
Effective Traffic Signal Control with Offline-to-Online Reinforcement Learning | https://ieeexplore.ieee.org/document/10341718/ | [
"Jinming Ma",
"Feng Wu",
"Jinming Ma",
"Feng Wu"
] | Reinforcement learning (RL) has emerged as a promising approach for optimizing traffic signal control (TSC) to ensure the efficient operation of transportation networks. However, the traditional trial-and-error technique in RL is usually impractical in real-world applications. Offline RL, which trains models using pre-collected datasets, is a more practical approach. However, this presents challen... |
Learning from Symmetry: Meta-Reinforcement Learning with Symmetrical Behaviors and Language Instructions | https://ieeexplore.ieee.org/document/10341769/ | [
"Xiangtong Yao",
"Zhenshan Bing",
"Genghang Zhuang",
"Kejia Chen",
"Hongkuan Zhou",
"Kai Huang",
"Alois Knoll",
"Xiangtong Yao",
"Zhenshan Bing",
"Genghang Zhuang",
"Kejia Chen",
"Hongkuan Zhou",
"Kai Huang",
"Alois Knoll"
] | Meta-reinforcement learning (meta-RL) is a promising approach that enables the agent to learn new tasks quickly. However, most meta-RL algorithms show poor generalization in multi-task scenarios due to the insufficient task information provided only by rewards. Language-conditioned meta-RL improves the generalization capability by matching language instructions with the agent's behaviors. While bo... |
A Multiplicative Value Function for Safe and Efficient Reinforcement Learning | https://ieeexplore.ieee.org/document/10342288/ | [
"Nick Bührer",
"Zhejun Zhang",
"Alexander Liniger",
"Fisher Yu",
"Luc Van Gool",
"Nick Bührer",
"Zhejun Zhang",
"Alexander Liniger",
"Fisher Yu",
"Luc Van Gool"
] | An emerging field of sequential decision problems is safe Reinforcement Learning (RL), where the objective is to maximize the reward while obeying safety constraints. Being able to handle constraints is essential for deploying RL agents in real-world environments, where constraint violations can harm the agent and the environment. To this end, we propose a safe model-free RL algorithm with a novel... |
Energy Constrained Multi-Agent Reinforcement Learning for Coverage Path Planning | https://ieeexplore.ieee.org/document/10341412/ | [
"Chenyang Zhao",
"Juan Liu",
"Suk-Un Yoon",
"Xinde Li",
"Heqing Li",
"Zhentong Zhang",
"Chenyang Zhao",
"Juan Liu",
"Suk-Un Yoon",
"Xinde Li",
"Heqing Li",
"Zhentong Zhang"
] | For multi-agent area coverage path planning problem, existing researches regard it as a combination of Traveling Salesman Problem (TSP) and Coverage Path Planning (CPP). However, these approaches have disadvantages of poor observation ability in online phase and high computational cost in offline phase, making it difficult to be applied to energy-constrained Unmanned Aerial Vehicles (UAVs) and adj... |
Air-M: A Visual Reality Many-Agent Reinforcement Learning Platform for Large-Scale Aerial Unmanned System | https://ieeexplore.ieee.org/document/10341405/ | [
"Jiabin Lou",
"Wenjun Wu",
"Shuhao Liao",
"Rongye Shi",
"Jiabin Lou",
"Wenjun Wu",
"Shuhao Liao",
"Rongye Shi"
] | Reinforcement learning for swarms of flying robots is a challenging task that requires a large number of data samples. Moreover, the problem of sim-to-real transfer has long been a challenge in robotics algorithm deployment. To address these issues, we propose Air-M, a platform that facilitates large-scale drone swarm learning in a distributed docker container environment and deployment in a virtu... |
Nonprehensile Planar Manipulation through Reinforcement Learning with Multimodal Categorical Exploration | https://ieeexplore.ieee.org/document/10341629/ | [
"Juan Del Aguila Ferrandis",
"João Moura",
"Sethu Vijayakumar",
"Juan Del Aguila Ferrandis",
"João Moura",
"Sethu Vijayakumar"
] | Developing robot controllers capable of achieving dexterous nonprehensile manipulation, such as pushing an object on a table, is challenging. The underactuated and hybrid-dynamics nature of the problem, further complicated by the uncertainty resulting from the frictional interactions, requires sophisticated control behaviors. Reinforcement Learning (RL) is a powerful framework for developing such ... |
Efficient Domain Coverage for Vehicles with Second-Order Dynamics via Multi-Agent Reinforcement Learning | https://ieeexplore.ieee.org/document/10341748/ | [
"Xinyu Zhao",
"Razvan C. Fetecau",
"Mo Chen",
"Xinyu Zhao",
"Razvan C. Fetecau",
"Mo Chen"
] | Collaborative autonomous multi-agent systems covering a specified area have many potential applications. Traditional approaches for such problems involve designing model-based control policies; however, state-of-the-art classical control policy still exhibits a large degree of sub-optimality. We present a combined reinforcement learning (RL) and control approach for the multi-agent coverage proble... |
Domains as Objectives: Multi-Domain Reinforcement Learning with Convex-Coverage Set Learning for Domain Uncertainty Awareness | https://ieeexplore.ieee.org/document/10342236/ | [
"Wendyam Eric Lionel Ilboudo",
"Taisuke Kobayashi",
"Takamitsu Matsubara",
"Wendyam Eric Lionel Ilboudo",
"Taisuke Kobayashi",
"Takamitsu Matsubara"
] | Domain randomization (DR) is a powerful framework that has allowed the transfer of policies from randomized domain (a.k.a. simulation) to real robots with little to no retraining requirement. However, because the policy has to perform well for many different domain conditions, DR tends to produce sub-optimal policies that can be too conservative on the target real system. This problem is further e... |
PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social Dilemmas | https://ieeexplore.ieee.org/document/10341884/ | [
"Shahab Nikkhoo",
"Zexin Li",
"Aritra Samanta",
"Yufei Li",
"Cong Liu",
"Shahab Nikkhoo",
"Zexin Li",
"Aritra Samanta",
"Yufei Li",
"Cong Liu"
] | Recent research has demonstrated the potential of reinforcement learning (RL) in enabling effective multi-robot collaboration, particularly in social dilemmas where robots face a trade-off between self-interests and collective benefits. However, environmental factors such as miscommunication and adversarial robots can impact cooperation, making it crucial to explore how multi-robot communication c... |
A Robust and Constrained Multi-Agent Reinforcement Learning Electric Vehicle Rebalancing Method in AMoD Systems | https://ieeexplore.ieee.org/document/10342342/ | [
"Sihong He",
"Yue Wang",
"Shuo Han",
"Shaofeng Zou",
"Fei Miao",
"Sihong He",
"Yue Wang",
"Shuo Han",
"Shaofeng Zou",
"Fei Miao"
] | Electric vehicles (EVs) play critical roles in autonomous mobility-on-demand (AMoD) systems, but their unique charging patterns increase the model uncertainties in AMoD systems (e.g. state transition probability). Since there usually exists a mismatch between the training and test/true environments, incorporating model uncertainty into system design is of critical importance in real-world applicat... |
Real-Time Model-Free Deep Reinforcement Learning for Force Control of a Series Elastic Actuator | https://ieeexplore.ieee.org/document/10341751/ | [
"Ruturaj Sambhus",
"Aydin Gokce",
"Stephen Welch",
"Connor W. Herron",
"Alexander Leonessa",
"Ruturaj Sambhus",
"Aydin Gokce",
"Stephen Welch",
"Connor W. Herron",
"Alexander Leonessa"
] | Many state-of-the-art robotic applications utilize series elastic actuators (SEAs) with closed-loop force control to achieve complex tasks such as walking, lifting, and manipulation. Model-free PID control methods are more prone to instability due to nonlinearities in the SEA where cascaded model-based robust controllers can remove these effects to achieve stable force control. However, these mode... |
An Approach to Design a Biomechanically-Inspired Reward Function to Solve a Patience Cube Under Reinforcement Learning Framework | https://ieeexplore.ieee.org/document/10341831/ | [
"Janghyeon Kim",
"Ho-Jin Jung",
"Dae Han Sim",
"Ji-Hyeon Yoo",
"Song Woo Kim",
"Han Ul Yoon",
"Janghyeon Kim",
"Ho-Jin Jung",
"Dae Han Sim",
"Ji-Hyeon Yoo",
"Song Woo Kim",
"Han Ul Yoon"
] | This paper presents an approach to design a reward function by adopting both control theoretic and biomechanical perspectives. In reinforcement learning (RL), a reward function plays a crucial role for an RL agent training; especially, a task learning time and a task performance. Accordingly, designing a reward function becomes a key issue to train an RL agent generating human-like policy/strategy... |
MaskBEV: Joint Object Detection and Footprint Completion for Bird's-Eye View 3D Point Clouds | https://ieeexplore.ieee.org/document/10342294/ | [
"William Guimont-Martin",
"Jean-Michel Fortin",
"François Pomerleau",
"Philippe Giguère",
"William Guimont-Martin",
"Jean-Michel Fortin",
"François Pomerleau",
"Philippe Giguère"
] | Recent works in object detection in LiDAR point clouds mostly focus on predicting bounding boxes around objects. This prediction is commonly achieved using anchor-based or anchor-free detectors that predict bounding boxes, requiring significant explicit prior knowledge about the objects to work properly. To remedy these limitations, we propose MaskBEV, a bird's-eye view (BEV) mask-based object det... |
Disentangled Discriminator for Unsupervised Domain Adaptation on Object Detection | https://ieeexplore.ieee.org/document/10341878/ | [
"Yangguang Zhu",
"Ping Guo",
"Haoran Wei",
"Xin Zhao",
"Xiangbin Wu",
"Yangguang Zhu",
"Ping Guo",
"Haoran Wei",
"Xin Zhao",
"Xiangbin Wu"
] | Object detection plays an important role in computer vision tasks such as autonomous driving, robotics, etc. Typically, a detection model is firstly trained on collected data and then deployed in real world. However, the discrepancy exists between training (source) and testing (target) data, which degrades the detection model's performance in the real world. To mitigate the negative effects, Unsup... |
Open-Vocabulary Affordance Detection in 3D Point Clouds | https://ieeexplore.ieee.org/document/10341553/ | [
"Toan Nguyen",
"Minh Nhat Vu",
"An Vuong",
"Dzung Nguyen",
"Thieu Vo",
"Ngan Le",
"Anh Nguyen",
"Toan Nguyen",
"Minh Nhat Vu",
"An Vuong",
"Dzung Nguyen",
"Thieu Vo",
"Ngan Le",
"Anh Nguyen"
] | Affordance detection is a challenging problem with a wide variety of robotic applications. Traditional affordance detection methods are limited to a predefined set of affordance labels, hence potentially restricting the adaptability of intelligent robots in complex and dynamic environments. In this paper, we present the Open-Vocabulary Affordance Detection (OpenAD) method, which is capable of dete... |
EvCenterNet: Uncertainty Estimation for Object Detection Using Evidential Learning | https://ieeexplore.ieee.org/document/10341826/ | [
"Monish R. Nallapareddy",
"Kshitij Sirohi",
"Paulo L. J. Drews",
"Wolfram Burgard",
"Chih-Hong Cheng",
"Abhinav Valada",
"Monish R. Nallapareddy",
"Kshitij Sirohi",
"Paulo L. J. Drews",
"Wolfram Burgard",
"Chih-Hong Cheng",
"Abhinav Valada"
] | Uncertainty estimation is crucial in safety-critical settings such as automated driving as it provides valuable information for several downstream tasks including high-level decision making and path planning. In this work, we propose EvCenterNet, a novel uncertainty-aware 2D object detection framework using evidential learning to directly estimate both classification and regression uncertainties. ... |
SemanticBEVFusion: Rethinking LiDAR-Camera Fusion in Unified Bird's-Eye View Representation for 3D Object Detection | https://ieeexplore.ieee.org/document/10342368/ | [
"Qi Jiang",
"Hao Sun",
"Qi Jiang",
"Hao Sun"
] | LiDAR and cameras are two essential sensors for 3D object detection in autonomous driving. LiDAR provides accurate and reliable 3D geometry information while the camera provides rich texture with color. Despite the increasing popularity of fusing these two complementary sensors, the challenge remains in how to effectively fuse 3D LiDAR point cloud with 2D camera images. Recent methods focus on poi... |
RFDNet: Real-Time 3D Object Detection Via Range Feature Decoration | https://ieeexplore.ieee.org/document/10341482/ | [
"Hongda Chang",
"Lu Wang",
"Jun Cheng",
"Hongda Chang",
"Lu Wang",
"Jun Cheng"
] | High-performance real-time 3D object detection is crucial in autonomous driving perception systems. Voxel-or point-based 3D object detectors are highly accurate but inefficient and difficult to deploy, while other methods use 2D projection views to improve efficiency, but information loss usually degrades performance. To balance effectiveness and efficiency, we propose a scheme called RFDNet that ... |
Object-Level Unknown Obstacle Detection | https://ieeexplore.ieee.org/document/10342306/ | [
"Chuan-Yuan Huang",
"Cheng-Tsung Chen",
"Yu-An Chen",
"Kuan-Wen Chen",
"Chuan-Yuan Huang",
"Cheng-Tsung Chen",
"Yu-An Chen",
"Kuan-Wen Chen"
] | This paper presents a novel method for object-level unknown obstacle detection in driving scenes that reduces false positives. The proposed method combines existing anomaly detectors, depth estimation, and object detection techniques to achieve object-level predictions. Our method can predict anomalies as bound-box instance detections. These bounding boxes can then be used to refine anomaly detect... |
BSH-Det3D: Improving 3D Object Detection with BEV Shape Heatmap | https://ieeexplore.ieee.org/document/10341930/ | [
"You Shen",
"Yunzhou Zhang",
"Yanmin Wu",
"Zhenyu Wang",
"Linghao Yang",
"Sonya Coleman",
"Dermot Kerr",
"You Shen",
"Yunzhou Zhang",
"Yanmin Wu",
"Zhenyu Wang",
"Linghao Yang",
"Sonya Coleman",
"Dermot Kerr"
] | The progress of LiDAR-based 3D object detection has significantly enhanced developments in autonomous driving and robotics. However, due to the limitations of LiDAR sensors, object shapes suffer from deterioration in occluded and distant areas, which creates a fundamental challenge to 3D perception. Existing methods estimate specific 3D shapes and achieve remarkable performance. However, these met... |
I3DOD: Towards Incremental 3D Object Detection via Prompting | https://ieeexplore.ieee.org/document/10341834/ | [
"Wenqi Liang",
"Gan Sun",
"Chenxi Liu",
"Jiahua Dong",
"Kangru Wang",
"Wenqi Liang",
"Gan Sun",
"Chenxi Liu",
"Jiahua Dong",
"Kangru Wang"
] | 3D object detection have achieved significant performance in many fields, e.g., robotics system, autonomous driving, and augmented reality. However, most existing methods could cause catastrophic forgetting of old classes when performing on the class-incremental scenarios. Meanwhile, the current class-incremental 3D object detection methods neglect the relationships between the object localization... |
SpinDOE: A Ball Spin Estimation Method for Table Tennis Robot | https://ieeexplore.ieee.org/document/10342178/ | [
"Thomas Gossard",
"Jonas Tebbe",
"Andreas Ziegler",
"Andreas Zell",
"Thomas Gossard",
"Jonas Tebbe",
"Andreas Ziegler",
"Andreas Zell"
] | Spin plays a considerable role in table tennis, making a shot's trajectory harder to read and predict. However, the spin is challenging to measure because of the ball's high velocity and the magnitude of the spin values. Existing methods either require extremely high framerate cameras or are unreliable because they use the ball's logo, which may not always be visible. Because of this, many table t... |
Enhancing Fine-Grained 3D Object Recognition Using Hybrid Multi-Modal Vision Transformer-CNN Models | https://ieeexplore.ieee.org/document/10342235/ | [
"Songsong Xiong",
"Georgios Tziafas",
"Hamidreza Kasaei",
"Songsong Xiong",
"Georgios Tziafas",
"Hamidreza Kasaei"
] | Robots operating in human-centered environments, such as retail stores, restaurants, and households, are often required to distinguish between similar objects in different contexts with a high degree of accuracy. However, fine-grained object recognition remains a challenge in robotics due to the high intra-category and low inter-category dissimilarities. In addition, the limited number of fine-gra... |
ScAR: Scaling Adversarial Robustness for LiDAR Object Detection | https://ieeexplore.ieee.org/document/10341583/ | [
"Xiaohu Lu",
"Hayder Radha",
"Xiaohu Lu",
"Hayder Radha"
] | The adversarial robustness of a model is its ability to resist adversarial attacks in the form of small perturbations to input data. Universal adversarial attack methods such as Fast Sign Gradient Method (FSGM) [1] and Projected Gradient Descend (PGD) [2] are popular for LiDAR object detection, but they are often deficient compared to task-specific adversarial attacks. Additionally, these universa... |
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