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TOP-JAM: A bio-inspired topology-based model of joint attention for human-robot interaction | https://ieeexplore.ieee.org/document/10160488/ | [
"Hendry Ferreira Chame",
"Aurélie Clodic",
"Rachid Alami",
"Hendry Ferreira Chame",
"Aurélie Clodic",
"Rachid Alami"
] | Coexisting with others and interacting in society implies sharing knowledge and attention about world objects, events, features, episodes, and even imagination or abstract ideas in time and space. Inspired by human phenomenological, cognitive and behavioral research, this work focuses on the study of joint attention (JA) for human-robot interaction (HRI), based on two main assumptions: a) the perc... |
NOPA: Neurally-guided Online Probabilistic Assistance for Building Socially Intelligent Home Assistants | https://ieeexplore.ieee.org/document/10161352/ | [
"Xavier Puig",
"Tianmin Shu",
"Joshua B. Tenenbaum",
"Antonio Torralba",
"Xavier Puig",
"Tianmin Shu",
"Joshua B. Tenenbaum",
"Antonio Torralba"
] | In this work, we study how to build socially intelligent robots to assist people in their homes. In particular, we focus on assistance with online goal inference, where robots must simultaneously infer humans' goals and how to help them achieve those goals. Prior assistance methods either lack the adaptivity to adjust helping strategies (i.e., when and how to help) in response to uncertainty about... |
Embodied Referring Expression for Manipulation Question Answering in Interactive Environment | https://ieeexplore.ieee.org/document/10160748/ | [
"Qie Sima",
"Sinan Tan",
"Huaping Liu",
"Fuchun Sun",
"Weifeng Xu",
"Ling Fu",
"Qie Sima",
"Sinan Tan",
"Huaping Liu",
"Fuchun Sun",
"Weifeng Xu",
"Ling Fu"
] | Embodied agents are expected to perform more complicated tasks in an interactive environment, with the progress of Embodied AI in recent years. Existing embodied tasks including Embodied Referring Expression (ERE) and other QA-form tasks mainly focuses on interaction in term of linguistic instruction. Therefore, enabling the agent to manipulate objects in the environment for exploration actively h... |
Congestion Prediction for Large Fleets of Mobile Robots | https://ieeexplore.ieee.org/document/10161554/ | [
"Ge Yu",
"Michael T. Wolf",
"Ge Yu",
"Michael T. Wolf"
] | This paper introduces a deep learning (DL) approach to predicting congestion delays in large multi-robot systems. The problem is motivated by real-world problems in modern logistics automation, such as a warehouse with hundreds to thousands of coordinated mobile robots. Here, the large scale, the complexity of the control software, and the uncertainties of the robots' dynamics make direct (simulat... |
Decentralised Active Perception in Continuous Action Spaces for the Coordinated Escort Problem | https://ieeexplore.ieee.org/document/10161026/ | [
"Rhett Hull",
"Ki Myung Brian Lee",
"Jennifer Wakulicz",
"Chanyeol Yoo",
"James McMahon",
"Bryan Clarke",
"Stuart Anstee",
"Jijoong Kim",
"Robert Fitch",
"Rhett Hull",
"Ki Myung Brian Lee",
"Jennifer Wakulicz",
"Chanyeol Yoo",
"James McMahon",
"Bryan Clarke",
"Stuart Anstee",
"Jijoong Kim",
"Robert Fitch"
] | We consider the coordinated escort problem, where a decentralised team of supporting robots implicitly assist the mission of higher-value principal robots. The defining challenge is how to evaluate the effect of supporting robots' actions on the principal robots' mission. To capture this effect, we define two novel auxiliary reward functions for supporting robots called satisfaction improvement an... |
Socially Fair Coverage Control | https://ieeexplore.ieee.org/document/10160988/ | [
"Matthew Malencia",
"George Pappas",
"Vijay Kumar",
"Matthew Malencia",
"George Pappas",
"Vijay Kumar"
] | We investigate and develop algorithms for social fairness in coverage control problems. Existing coverage control methods are efficient, optimizing the average expected distance from any event to the nearest robot. However, in societal applications like disaster response or transportation, these conventional objectives lead to disparate coverage costs with respect to different groups within a popu... |
Exploiting Trust for Resilient Hypothesis Testing with Malicious Robots | https://ieeexplore.ieee.org/document/10160385/ | [
"Matthew Cavorsi",
"Orhan Eren Akgün",
"Michal Yemini",
"Andrea J. Goldsmith",
"Stephanie Gil",
"Matthew Cavorsi",
"Orhan Eren Akgün",
"Michal Yemini",
"Andrea J. Goldsmith",
"Stephanie Gil"
] | We develop a resilient binary hypothesis testing frame-work for decision making in adversarial multi-robot crowdsensing tasks. This framework exploits stochastic trust observations between robots to arrive at tractable, resilient decision making at a centralized Fusion Center (FC) even when i) there exist malicious robots in the network and their number may be larger than the number of legitimate ... |
Obscuring Objectives with Pareto-Optimal Privacy-Aware Trajectories in Multi-Robot Coverage | https://ieeexplore.ieee.org/document/10160520/ | [
"Brennan Brodt",
"Alyssa Pierson",
"Brennan Brodt",
"Alyssa Pierson"
] | This paper proposes an algorithm for generating Pareto-optimal privacy-aware trajectories for multi-robot coverage. Our approach utilizes a genetic algorithm to generate a set of modified trajectories for a team of robots that wishes to obscure its goal from an observer. A novel velocity-constrained crossover algorithm ensures all child trajectories are feasible for a holonomic vehicle. The Pareto... |
Safe and Distributed Multi-Agent Motion Planning under Minimum Speed Constraints | https://ieeexplore.ieee.org/document/10160280/ | [
"Inkyu Jang",
"Jungwon Park",
"H. Jin Kim",
"Inkyu Jang",
"Jungwon Park",
"H. Jin Kim"
] | The motion planning problem for multiple unstop-pable agents is of interest in many robotics applications, for example, autonomous traffic management for multiple fixed-wing aircraft. Unfortunately, many of the existing algorithms cannot provide safety for such agents, because they require the agents to be able to brake to a complete stop for safety and feasibility insurance. In this paper, we pre... |
Minimally Constrained Multi-Robot Coordination with Line-of-Sight Connectivity Maintenance | https://ieeexplore.ieee.org/document/10161401/ | [
"Yupeng Yang",
"Yiwei Lyu",
"Wenhao Luo",
"Yupeng Yang",
"Yiwei Lyu",
"Wenhao Luo"
] | In this paper, we consider a team of mobile robots executing simultaneously multiple behaviors by different subgroups, while maintaining global and subgroup line-of-sight (LOS) network connectivity that minimally constrains the original multi-robot behaviors. The LOS connectivity between pairwise robots is preserved when two robots stay within the limited communication range and their LOS remains ... |
Relay Pursuit for Multirobot Target Tracking on Tile Graphs | https://ieeexplore.ieee.org/document/10161532/ | [
"Shashwata Mandal",
"Sourabh Bhattacharya",
"Shashwata Mandal",
"Sourabh Bhattacharya"
] | In this work, we address a visbility-based target tracking problem in a polygonal environment in which a group of mobile observers try to maintain a line-of-sight with a mobile intruder. We build a bridge between data mining and visibility-based tracking using a novel tiling scheme for the polygon. First, we propose a tracking strategy for a team of guards located on the tiles to dynamically track... |
Passivity-based Decentralized Control for Collaborative Grasping of Under-Actuated Aerial Manipulators | https://ieeexplore.ieee.org/document/10160334/ | [
"Jinyeong Jeong",
"Min Jun Kim",
"Jinyeong Jeong",
"Min Jun Kim"
] | This paper proposes a decentralized passive impedance control scheme for collaborative grasping using under-actuated aerial manipulators (AMs). The AM system is formulated, using a proper coordinate transformation, as an inertially decoupled dynamics with which a passivity-based control design is conducted. Since the interaction for grasping can be interpreted as a feedback interconnection of pass... |
Distributed barrier function-enabled human-in-the-loop control for multi-robot systems | https://ieeexplore.ieee.org/document/10160974/ | [
"Victor Nan Fernandez-Ayala",
"Xiao Tan",
"Dimos V. Dimarogonas",
"Victor Nan Fernandez-Ayala",
"Xiao Tan",
"Dimos V. Dimarogonas"
] | In this work, we propose a distributed control scheme for multi-robot systems in the presence of multiple constraints using control barrier functions. The proposed scheme expands previous work where only one single constraint can be handled. Here we show how to transform multiple constraints to a collective one using a smoothly approximated minimum function. Additionally, human-in-the-loop control... |
LEMURS: Learning Distributed Multi-Robot Interactions | https://ieeexplore.ieee.org/document/10161328/ | [
"Eduardo Sebastián",
"Thai Duong",
"Nikolay Atanasov",
"Eduardo Montijano",
"Carlos Sagüés",
"Eduardo Sebastián",
"Thai Duong",
"Nikolay Atanasov",
"Eduardo Montijano",
"Carlos Sagüés"
] | This paper presents LEMURS, an algorithm for learning scalable multi-robot control policies from cooperative task demonstrations. We propose a port-Hamiltonian description of the multi-robot system to exploit universal physical constraints in interconnected systems and achieve closed-loop stability. We represent a multi-robot control policy using an architecture that combines self-attention mechan... |
Multi-Agent Active Search using Detection and Location Uncertainty | https://ieeexplore.ieee.org/document/10161017/ | [
"Arundhati Banerjee",
"Ramina Ghods",
"Jeff Schneider",
"Arundhati Banerjee",
"Ramina Ghods",
"Jeff Schneider"
] | Active search, in applications like environment monitoring or disaster response missions, involves autonomous agents detecting targets in a search space using decision making algorithms that adapt to the history of their observations. Active search algorithms must contend with two types of uncertainty: detection uncertainty and location uncertainty. The more common approach in robotics is to focus... |
HMAAC: Hierarchical Multi-Agent Actor-Critic for Aerial Search with Explicit Coordination Modeling | https://ieeexplore.ieee.org/document/10161019/ | [
"Chuanneng Sun",
"Songjun Huang",
"Dario Pompili",
"Chuanneng Sun",
"Songjun Huang",
"Dario Pompili"
] | Unmanned Aerial Vehicles (UAVs) have become prevalent in Search-And-Rescue (SAR) missions. However, existing solutions to the control and coordination of UAV s are mostly limited to specific environments and are not robust to handle unreliable/unstable communications. To deal with these challenges, Hierarchical Multi-Agent Actor-Critic (HMAAC) framework is proposed where a high-level policy is pla... |
GUTS: Generalized Uncertainty-Aware Thompson Sampling for Multi-Agent Active Search | https://ieeexplore.ieee.org/document/10160597/ | [
"Nikhil Angad Bakshi",
"Tejus Gupta",
"Ramina Ghods",
"Jeff Schneider",
"Nikhil Angad Bakshi",
"Tejus Gupta",
"Ramina Ghods",
"Jeff Schneider"
] | Robotic solutions for quick disaster response are essential to ensure minimal loss of life, especially when the search area is too dangerous or too vast for human rescuers. We model this problem as an asynchronous multi-agent active-search task where each robot aims to efficiently seek objects of interest (OOIs) in an unknown environment. This formulation addresses the requirement that search miss... |
CLIO: a Novel Robotic Solution for Exploration and Rescue Missions in Hostile Mountain Environments | https://ieeexplore.ieee.org/document/10160440/ | [
"Michele Focchi",
"Mohamed Bensaadallah",
"Marco Frego",
"Angelika Peer",
"Daniele Fontanelli",
"Andrea Del Prete",
"Luigi Palopoli",
"Michele Focchi",
"Mohamed Bensaadallah",
"Marco Frego",
"Angelika Peer",
"Daniele Fontanelli",
"Andrea Del Prete",
"Luigi Palopoli"
] | Rescue missions in mountain environments are hardly achievable by standard legged robots—because of the high slopes—or by flying robots—because of limited payload capacity. We present a concept for a rope-aided climbing robot which can negotiate up-to-vertical slopes and carry heavy payloads. The robot is attached to the mountain through a rope, and it is equipped with a leg to push against the mo... |
Towards Efficient Gas Leak Detection in Built Environments: Data-Driven Plume Modeling for Gas Sensing Robots | https://ieeexplore.ieee.org/document/10160816/ | [
"Wanting Jin",
"Faezeh Rahbar",
"Chiara Ercolani",
"Alcherio Martinoli",
"Wanting Jin",
"Faezeh Rahbar",
"Chiara Ercolani",
"Alcherio Martinoli"
] | The deployment of robots for Gas Source Localization (GSL) tasks in hazardous scenarios significantly reduces the risk to humans and animals. Gas sensing using mobile robots focuses primarily on simplified scenarios, due to the complexity of gas dispersion, with a current trend towards tackling more complex environments. However, most state-of-art GSL algorithms for environments with obstacles onl... |
Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs | https://ieeexplore.ieee.org/document/10160815/ | [
"Youya Xia",
"Josephine Monica",
"Wei-Lun Chao",
"Bharath Hariharan",
"Kilian Q Weinberger",
"Mark Campbell",
"Youya Xia",
"Josephine Monica",
"Wei-Lun Chao",
"Bharath Hariharan",
"Kilian Q Weinberger",
"Mark Campbell"
] | A self-driving car must be able to reliably handle adverse weather conditions (e.g., snowy) to operate safely. In this paper, we investigate the idea of turning sensor inputs (i.e., images) captured in an adverse condition into a benign one (i.e., sunny), upon which the downstream tasks (e.g., semantic segmentation) can attain high accuracy. Prior work primarily formulates this as an unpaired imag... |
Small-shot Multi-modal Distillation for Vision-based Autonomous Steering | https://ieeexplore.ieee.org/document/10160803/ | [
"Yu Shen",
"Luyu Yang",
"Xijun Wang",
"Ming C. Lin",
"Yu Shen",
"Luyu Yang",
"Xijun Wang",
"Ming C. Lin"
] | In this paper, we propose a novel learning framework for autonomous systems that uses a small amount of “auxiliary information” that complements the learning of the main modality, called “small-shot auxiliary modality distillation network (AMD-S-Net)”. The AMD-S-Net contains a two-stream framework design that can fully extract information from different types of data (i.e., paired/unpaired multi-m... |
SceneCalib: Automatic Targetless Calibration of Cameras and Lidars in Autonomous Driving | https://ieeexplore.ieee.org/document/10161316/ | [
"Ayon Sen",
"Gang Pan",
"Anton Mitrokhin",
"Ashraful Islam",
"Ayon Sen",
"Gang Pan",
"Anton Mitrokhin",
"Ashraful Islam"
] | Accurate camera-to-lidar calibration is a requirement for sensor data fusion in many 3D perception tasks. In this paper, we present SceneCalib, a novel method for simultaneous self-calibration of extrinsic and intrinsic parameters in a system containing multiple cameras and a lidar sensor. Existing methods typically require specially designed calibration targets and human operators, or they only a... |
Unsupervised Road Anomaly Detection with Language Anchors | https://ieeexplore.ieee.org/document/10160470/ | [
"Beiwen Tian",
"Mingdao Liu",
"Huan-ang Gao",
"Pengfei Li",
"Hao Zhao",
"Guyue Zhou",
"Beiwen Tian",
"Mingdao Liu",
"Huan-ang Gao",
"Pengfei Li",
"Hao Zhao",
"Guyue Zhou"
] | Road anomaly detection is critical to safe autonomous driving, because current road scene understanding models are usually trained in a closed-set manner and fail to identify unknown objects. What's worse, it is difficult, if not impossible, to collect a large-scale dataset with anomaly annotations. So this paper studies unsupervised anomaly detection which finds out anomaly regions using scene pa... |
Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning | https://ieeexplore.ieee.org/document/10161155/ | [
"Boris Ivanovic",
"James Harrison",
"Marco Pavone",
"Boris Ivanovic",
"James Harrison",
"Marco Pavone"
] | Learning-based behavior prediction methods are increasingly being deployed in real-world autonomous systems, e.g., in fleets of self-driving vehicles, which are beginning to commercially operate in major cities across the world. Despite their advancements, however, the vast majority of prediction systems are specialized to a set of well-explored geographic regions or operational design domains, co... |
Interaction-Aware Trajectory Planning for Autonomous Vehicles with Analytic Integration of Neural Networks into Model Predictive Control | https://ieeexplore.ieee.org/document/10160890/ | [
"Piyush Gupta",
"David Isele",
"Donggun Lee",
"Sangjae Bae",
"Piyush Gupta",
"David Isele",
"Donggun Lee",
"Sangjae Bae"
] | Autonomous vehicles (AVs) must share the driving space with other drivers and often employ conservative motion planning strategies to ensure safety. These conservative strategies can negatively impact AV's performance and significantly slow traffic throughput. Therefore, to avoid conservatism, we design an interaction-aware motion planner for the ego vehicle (AV) that interacts with surrounding ve... |
GoRela: Go Relative for Viewpoint-Invariant Motion Forecasting | https://ieeexplore.ieee.org/document/10160984/ | [
"Alexander Cui",
"Sergio Casas",
"Kelvin Wong",
"Simon Suo",
"Raquel Urtasun",
"Alexander Cui",
"Sergio Casas",
"Kelvin Wong",
"Simon Suo",
"Raquel Urtasun"
] | The task of motion forecasting is critical for self- driving vehicles (SDV s) to be able to plan a safe maneuver. Towards this goal, modern approaches reason about the map, the agents' past trajectories and their interactions in order to produce accurate forecasts. The predominant approach has been to encode the map and other agents in the reference frame of each target agent. However, this approa... |
RGB-Event Fusion for Moving Object Detection in Autonomous Driving | https://ieeexplore.ieee.org/document/10161563/ | [
"Zhuyun Zhou",
"Zongwei Wu",
"Rémi Boutteau",
"Fan Yang",
"Cédric Demonceaux",
"Dominique Ginhac",
"Zhuyun Zhou",
"Zongwei Wu",
"Rémi Boutteau",
"Fan Yang",
"Cédric Demonceaux",
"Dominique Ginhac"
] | Moving Object Detection (MOD) is a critical vision task for successfully achieving safe autonomous driving. Despite plausible results of deep learning methods, most existing approaches are only frame-based and may fail to reach reasonable performance when dealing with dynamic traffic participants. Recent advances in sensor technologies, especially the Event camera, can naturally complement the con... |
Self-Entanglement-Free Tethered Path Planning for Non-Particle Differential-Driven Robot | https://ieeexplore.ieee.org/document/10160549/ | [
"Tong Yang",
"Jiangpin Liu",
"Yue Wang",
"Rong Xiong",
"Tong Yang",
"Jiangpin Liu",
"Yue Wang",
"Rong Xiong"
] | A novel mechanism to derive self-entanglement-free path for tethered differential-driven robots is proposed in this work. The problem is tailored to the applications of tethered robots without an omni-directional tether re-tractor which is often encountered when an omni-directional tether retracting mechanism is incapable of being jointly equipped with other geometrically complex devices (e.g. a m... |
Operating with Inaccurate Models by Integrating Control-Level Discrepancy Information into Planning | https://ieeexplore.ieee.org/document/10161389/ | [
"Ellis Ratner",
"Claire J. Tomlin",
"Maxim Likhachev",
"Ellis Ratner",
"Claire J. Tomlin",
"Maxim Likhachev"
] | Typical robotic systems rely on models for planning. Therefore, the quality of the robot's behavior is heavily dependent on how accurately the model can predict the outcome of the robot's actions in the environment. A challenge, however, is that no model is perfect; moreover, we often do not know where discrepancies between the model's prediction and the actual outcome occur prior to observing exe... |
Approximation Algorithms for Robot Tours in Random Fields with Guaranteed Estimation Accuracy | https://ieeexplore.ieee.org/document/10160912/ | [
"Shamak Dutta",
"Nils Wilde",
"Pratap Tokekar",
"Stephen L. Smith",
"Shamak Dutta",
"Nils Wilde",
"Pratap Tokekar",
"Stephen L. Smith"
] | We study the sample placement and shortest tour problem for robots tasked with mapping environmental phenomena modeled as stationary random fields. The objective is to minimize the resources used (samples or tour length) while guaranteeing estimation accuracy. We give approximation algorithms for both problems in convex environments. These improve previously known results, both in terms of theoret... |
Real-Time Fast Marching Tree for Mobile Robot Motion Planning in Dynamic Environments | https://ieeexplore.ieee.org/document/10160595/ | [
"Jefferson Silveira",
"Kleber Cabral",
"Sidney Givigi",
"Joshua A. Marshall",
"Jefferson Silveira",
"Kleber Cabral",
"Sidney Givigi",
"Joshua A. Marshall"
] | This paper proposes the Real-Time Fast Marching Tree (RT-FMT), a real-time planning algorithm that features local and global path generation, multiple-query planning, and dynamic obstacle avoidance. During the search, RT-FMT quickly looks for the global solution and, in the meantime, generates local paths that can be used by the robot to start execution faster. In addition, our algorithm constantl... |
Efficient Optimal Planning in non-FIFO Time-Dependent Flow Fields | https://ieeexplore.ieee.org/document/10161424/ | [
"James Ju Heon Lee",
"Chanyeol Yoo",
"Stuart Anstee",
"Robert Fitch",
"James Ju Heon Lee",
"Chanyeol Yoo",
"Stuart Anstee",
"Robert Fitch"
] | We propose an algorithm for solving the time-dependent shortest path problem in flow fields where the FIFO (first-in-first-out) assumption is violated. This problem variant is important for autonomous vehicles in the ocean, for example, that cannot arbitrarily hover in a fixed position and that are strongly influenced by time-varying ocean currents. Although polynomial-time solutions are available... |
Human-Guided Planning for Complex Manipulation Tasks Using the Screw Geometry of Motion | https://ieeexplore.ieee.org/document/10161130/ | [
"Dasharadhan Mahalingam",
"Nilanjan Chakraborty",
"Dasharadhan Mahalingam",
"Nilanjan Chakraborty"
] | In this paper, we present a novel method of motion planning for performing complex manipulation tasks by using human demonstration and exploiting the screw geometry of motion. We consider complex manipulation tasks where there are constraints on the motion of the end effector of the robot. Examples of such tasks include opening a door, opening a drawer, transferring granular material from one cont... |
Towards Efficient Trajectory Generation for Ground Robots beyond 2D Environment | https://ieeexplore.ieee.org/document/10160330/ | [
"Jingping Wang",
"Long Xu",
"Haoran Fu",
"Zehui Meng",
"Chao Xu",
"Yanjun Cao",
"Ximin Lyu",
"Fei Gao",
"Jingping Wang",
"Long Xu",
"Haoran Fu",
"Zehui Meng",
"Chao Xu",
"Yanjun Cao",
"Ximin Lyu",
"Fei Gao"
] | With the development of robotics, ground robots are no longer limited to planar motion. Passive height variation due to complex terrain and active height control provided by special structures on robots require a more general navigation planning framework beyond 2D. Existing methods rarely considers both simultaneously, limiting the capabilities and applications of ground robots. In this paper, we... |
Concentration of Measure Phenomenon and its Implications for Sample-based Planning Algorithms in Very-High Dimensional Configuration Spaces | https://ieeexplore.ieee.org/document/10160286/ | [
"Joel M. Esposito",
"Joel M. Esposito"
] | In very high-dimensional $(\gg 10)$ spaces, a collection of points generated uniformly at random will concentrate very tightly about its expected value - defying intuition developed in low-dimensional spaces. This paper explores the implications of this for two major classes of sample-based robot motion planning algorithms: Rapidly Exploring Random Trees (RRTs) and Probabilistic Road Maps (PRMs). ... |
Safeguarding Learning-Based Planners Under Motion and Sensing Uncertainties Using Reachability Analysis | https://ieeexplore.ieee.org/document/10160457/ | [
"Akshay Shetty",
"Adam Dai",
"Alexandros Tzikas",
"Grace Gao",
"Akshay Shetty",
"Adam Dai",
"Alexandros Tzikas",
"Grace Gao"
] | Learning-based trajectory planners in robotics have attracted growing interest given their ability to plan for complex tasks. These planners are typically trained in simulation under nominal conditions before being implemented on real robots. However, in real settings, the presence of motion and sensing uncertainties causes the robot to deviate from planned reference trajectories potentially leadi... |
Risk-aware Spatio-temporal Logic Planning in Gaussian Belief Spaces | https://ieeexplore.ieee.org/document/10160973/ | [
"Matti Vahs",
"Christian Pek",
"Jana Tumova",
"Matti Vahs",
"Christian Pek",
"Jana Tumova"
] | In many real-world robotic scenarios, we cannot assume exact knowledge about a robot's state due to unmodeled dynamics or noisy sensors. Planning in belief space addresses this problem by tightly coupling perception and planning modules to obtain trajectories that take into account the environment's stochasticity. However, existing works are often limited to tasks such as the classic reach-avoid p... |
Density Planner: Minimizing Collision Risk in Motion Planning with Dynamic Obstacles using Density-based Reachability | https://ieeexplore.ieee.org/document/10161378/ | [
"Laura Lützow",
"Yue Meng",
"Andres Chavez Armijos",
"Chuchu Fan",
"Laura Lützow",
"Yue Meng",
"Andres Chavez Armijos",
"Chuchu Fan"
] | Uncertainty is prevalent in robotics. Due to measurement noise and complex dynamics, we cannot estimate the exact system and environment state. Since conservative motion planners are not guaranteed to find a safe control strategy in a crowded, uncertain environment, we propose a density-based method. Our approach uses a neural network and the Liouville equation to learn the density evolution for a... |
Sequential Bayesian Optimization for Adaptive Informative Path Planning with Multimodal Sensing | https://ieeexplore.ieee.org/document/10160859/ | [
"Joshua Ott",
"Edward Balaban",
"Mykel J. Kochenderfer",
"Joshua Ott",
"Edward Balaban",
"Mykel J. Kochenderfer"
] | Adaptive Informative Path Planning with Multi-modal Sensing (AIPPMS) considers the problem of an agent equipped with multiple sensors, each with different sensing accuracy and energy costs. The agent's goal is to explore the environment and gather information subject to its resource constraints in unknown, partially observable environments. Previous work has focused on the less general Adaptive In... |
Tree-structured Policy Planning with Learned Behavior Models | https://ieeexplore.ieee.org/document/10161419/ | [
"Yuxiao Chen",
"Peter Karkus",
"Boris Ivanovic",
"Xinshuo Weng",
"Marco Pavone",
"Yuxiao Chen",
"Peter Karkus",
"Boris Ivanovic",
"Xinshuo Weng",
"Marco Pavone"
] | Autonomous vehicles (AVs) need to reason about the multimodal behavior of neighboring agents while planning their own motion. Many existing trajectory planners seek a single trajectory that performs well under all plausible futures simultaneously, ignoring bi-directional interactions and thus leading to overly conservative plans. Policy planning, whereby the ego agent plans a policy that reacts to... |
Fast and Scalable Signal Inference for Active Robotic Source Seeking | https://ieeexplore.ieee.org/document/10161445/ | [
"Christopher E. Denniston",
"Oriana Peltzer",
"Joshua Ott",
"Sangwoo Moon",
"Sung-Kyun Kim",
"Gaurav S. Sukhatme",
"Mykel J. Kochenderfer",
"Mac Schwager",
"Ali-akbar Agha-mohammadi",
"Christopher E. Denniston",
"Oriana Peltzer",
"Joshua Ott",
"Sangwoo Moon",
"Sung-Kyun Kim",
"Gaurav S. Sukhatme",
"Mykel J. Kochenderfer",
"Mac Schwager",
"Ali-akbar Agha-mohammadi"
] | In active source seeking, a robot takes repeated measurements in order to locate a signal source in a cluttered and unknown environment. A key component of an active source seeking robot planner is a model that can produce estimates of the signal at unknown locations with uncertainty quantification. This model allows the robot to plan for future measurements in the environment. Traditionally, this... |
Active Inference for Autonomous Decision-Making with Contextual Multi-Armed Bandits | https://ieeexplore.ieee.org/document/10160593/ | [
"Shohei Wakayama",
"Nisar Ahmed",
"Shohei Wakayama",
"Nisar Ahmed"
] | In autonomous robotic decision-making under uncertainty, the tradeoff between exploitation and exploration of available options must be considered. If secondary information associated with options can be utilized, such decision-making problems can often be formulated as contextual multi-armed bandits (CMABs). In this study, we apply active inference, which has been actively studied in the field of... |
Covariance Steering for Uncertain Contact-rich Systems | https://ieeexplore.ieee.org/document/10160249/ | [
"Yuki Shirai",
"Devesh K. Jha",
"Arvind U. Raghunathan",
"Yuki Shirai",
"Devesh K. Jha",
"Arvind U. Raghunathan"
] | Planning and control for uncertain contact systems is challenging as it is not clear how to propagate uncertainty for planning. Contact-rich tasks can be modeled efficiently using complementarity constraints among other techniques. In this paper, we present a stochastic optimization technique with chance constraints for systems with stochastic complementarity constraints. We use a particle filter-... |
A congestion-aware path planning method considering crowd spatial-temporal anomalies for long-term autonomy of mobile robots | https://ieeexplore.ieee.org/document/10160252/ | [
"Zijian Ge",
"Jingjing Jiang",
"Matthew Coombes",
"Zijian Ge",
"Jingjing Jiang",
"Matthew Coombes"
] | A congestion-aware path planning method is pre-sented for mobile robots during long-term deployment in human occupied environments. With known spatial-temporal crowd patterns, the robot will navigate to its destination via less congested areas. Traditional traffic-aware routing methods do not consider spatial-temporal anomalies of macroscopic crowd behaviour that can deviate from the predicted cro... |
Risk-Aware Model Predictive Path Integral Control Using Conditional Value-at-Risk | https://ieeexplore.ieee.org/document/10161100/ | [
"Ji Yin",
"Zhiyuan Zhang",
"Panagiotis Tsiotras",
"Ji Yin",
"Zhiyuan Zhang",
"Panagiotis Tsiotras"
] | In this paper, we present a novel Model Predictive Control method for autonomous robot planning and control subject to arbitrary forms of uncertainty. The proposed Risk-Aware Model Predictive Path Integral (RA-MPPI) control utilizes the Conditional Value-at-Risk (CVaR) measure to generate optimal control actions for safety-critical robotic applications. Different from most existing Stochastic MPCs... |
Chance-Constrained Motion Planning with Event-Triggered Estimation | https://ieeexplore.ieee.org/document/10160940/ | [
"Anne Theurkauf",
"Qi Heng Ho",
"Roland Ilyes",
"Nisar Ahmed",
"Morteza Lahijanian",
"Anne Theurkauf",
"Qi Heng Ho",
"Roland Ilyes",
"Nisar Ahmed",
"Morteza Lahijanian"
] | We consider the problem of motion and communication planning under uncertainty with limited information from a remote sensor network. Because the remote sensors are power and bandwidth limited, we use event-triggered (ET) estimation to manage communication costs. We introduce a fast and efficient sampling-based planner which computes motion plans coupled with ET communication strategies that minim... |
STAP: Sequencing Task-Agnostic Policies | https://ieeexplore.ieee.org/document/10160220/ | [
"Christopher Agia",
"Toki Migimatsu",
"Jiajun Wu",
"Jeannette Bohg",
"Christopher Agia",
"Toki Migimatsu",
"Jiajun Wu",
"Jeannette Bohg"
] | Advances in robotic skill acquisition have made it possible to build general-purpose libraries of learned skills for downstream manipulation tasks. However, naively executing these skills one after the other is unlikely to succeed without accounting for dependencies between actions prevalent in longhorizon plans. We present Sequencing Task-Agnostic Policies (STAP), a scalable framework for trainin... |
A Multi-step Dynamics Modeling Framework For Autonomous Driving In Multiple Environments | https://ieeexplore.ieee.org/document/10161330/ | [
"Jason Gibson",
"Bogdan Vlahov",
"David Fan",
"Patrick Spieler",
"Daniel Pastor",
"Ali-akbar Agha-mohammadi",
"Evangelos A. Theodorou",
"Jason Gibson",
"Bogdan Vlahov",
"David Fan",
"Patrick Spieler",
"Daniel Pastor",
"Ali-akbar Agha-mohammadi",
"Evangelos A. Theodorou"
] | Modeling dynamics is often the first step to making a vehicle autonomous. While on-road autonomous vehicles have been extensively studied, off-road vehicles pose many challenging modeling problems. An off-road vehicle encounters highly complex and difficult-to-model terrain/vehicle interactions, as well as having complex vehicle dynamics of its own. These complexities can create challenges for eff... |
Self-adaptive Teaching-learning-based Optimizer with Improved RBF and Sparse Autoencoder for Complex Optimization Problems | https://ieeexplore.ieee.org/document/10160442/ | [
"Jing Bi",
"Ziqi Wang",
"Haitao Yuan",
"Junfei Qiao",
"Jia Zhang",
"MengChu Zhou",
"Jing Bi",
"Ziqi Wang",
"Haitao Yuan",
"Junfei Qiao",
"Jia Zhang",
"MengChu Zhou"
] | Evolutionary algorithms are commonly used to solve many complex optimization problems in such fields as robotics, industrial automation, and complex system design. Yet, their performance is limited when dealing with high-dimensional complex problems because they often require enormous computational resources to yield desired solutions, and they may easily trap into local optima. To solve this prob... |
Learning Neuro-symbolic Programs for Language Guided Robot Manipulation | https://ieeexplore.ieee.org/document/10160545/ | [
"Namasivayam K",
"Himanshu Singh",
"Vishal Bindal",
"Arnav Tuli",
"Vishwajeet Agrawal",
"Rahul Jain",
"Parag Singla",
"Rohan Paul",
"Namasivayam K",
"Himanshu Singh",
"Vishal Bindal",
"Arnav Tuli",
"Vishwajeet Agrawal",
"Rahul Jain",
"Parag Singla",
"Rohan Paul"
] | Given a natural language instruction and an input scene, our goal is to train a model to output a manipulation program that can be executed by the robot. Prior approaches for this task possess one of the following limitations: (i) rely on hand-coded symbols for concepts limiting generalization beyond those seen during training [1] (ii) infer action sequences from instructions but require dense sub... |
Real-Time Generative Grasping with Spatio-temporal Sparse Convolution | https://ieeexplore.ieee.org/document/10161529/ | [
"Timothy R. Player",
"Dongsik Chang",
"Li Fuxin",
"Geoffrey A. Hollinger",
"Timothy R. Player",
"Dongsik Chang",
"Li Fuxin",
"Geoffrey A. Hollinger"
] | Robots performing mobile manipulation in unstructured environments must identify grasp affordances quickly and with robustness to perception noise. Yet in domains such as underwater manipulation, where perception noise is severe, computation is constrained, and the environment is dynamic, existing techniques fail. They are too computationally demanding, or too sensitive to noise to allow for close... |
Keypoint-GraspNet: Keypoint-based 6-DoF Grasp Generation from the Monocular RGB-D input | https://ieeexplore.ieee.org/document/10161284/ | [
"Yiye Chen",
"Yunzhi Lin",
"Ruinian Xu",
"Patricio A. Vela",
"Yiye Chen",
"Yunzhi Lin",
"Ruinian Xu",
"Patricio A. Vela"
] | The success of 6-DoF grasp learning with point cloud input is tempered by the computational costs resulting from their unordered nature and pre-processing needs for reducing the point cloud to a manageable size. These properties lead to failure on small objects with low point cloud cardinality. Instead of point clouds, this manuscript explores grasp generation directly from the RGB-D image input. ... |
Pick2Place: Task-aware 6DoF Grasp Estimation via Object-Centric Perspective Affordance | https://ieeexplore.ieee.org/document/10160736/ | [
"Zhanpeng He",
"Nikhil Chavan-Dafle",
"Jinwook Huh",
"Shuran Song",
"Volkan Isler",
"Zhanpeng He",
"Nikhil Chavan-Dafle",
"Jinwook Huh",
"Shuran Song",
"Volkan Isler"
] | The choice of a grasp plays a critical role in the success of downstream manipulation tasks. Consider a task of placing an object in a cluttered scene; the majority of possible grasps may not be suitable for the desired placement. In this paper, we study the synergy between the picking and placing of an object in a cluttered scene to develop an algorithm for task-aware grasp estimation. We present... |
RGB-D Grasp Detection via Depth Guided Learning with Cross-modal Attention | https://ieeexplore.ieee.org/document/10161319/ | [
"Ran Qin",
"Haoxiang Ma",
"Boyang Gao",
"Di Huang",
"Ran Qin",
"Haoxiang Ma",
"Boyang Gao",
"Di Huang"
] | Planar grasp detection is one of the most fundamental tasks to robotic manipulation, and the recent progress of consumer-grade RGB-D sensors enables delivering more comprehensive features from both the texture and shape modalities. However, depth maps are generally of a relatively lower quality with much stronger noise compared to RGB images, making it challenging to acquire grasp depth and fuse m... |
Towards Generalized Robot Assembly through Compliance-Enabled Contact Formations | https://ieeexplore.ieee.org/document/10161073/ | [
"Andrew S. Morgan",
"Quentin Bateux",
"Mei Hao",
"Aaron M. Dollar",
"Andrew S. Morgan",
"Quentin Bateux",
"Mei Hao",
"Aaron M. Dollar"
] | Contact can be conceptualized as a set of constraints imposed on two bodies that are interacting with one another in some way. The nature of a contact, whether a point, line, or surface, dictates how these bodies are able to move with respect to one another given a force, and a set of contacts can provide either partial or full constraint on a body's motion. Decades of work have explored how to ex... |
Design of a Multimodal Fingertip Sensor for Dynamic Manipulation | https://ieeexplore.ieee.org/document/10160256/ | [
"Andrew SaLoutos",
"Elijah Stanger-Jones",
"Menglong Guo",
"Hongmin Kim",
"Sangbae Kim",
"Andrew SaLoutos",
"Elijah Stanger-Jones",
"Menglong Guo",
"Hongmin Kim",
"Sangbae Kim"
] | We introduce a spherical fingertip sensor for dynamic manipulation. It is based on barometric pressure and time-of-flight proximity sensors and is low-latency, compact, and physically robust. The sensor uses a trained neural network to estimate the contact location and three-axis contact forces based on data from the pressure sensors, which are embedded within the sensor's sphere of polyurethane r... |
TactoFind: A Tactile Only System for Object Retrieval | https://ieeexplore.ieee.org/document/10160289/ | [
"Sameer Pai",
"Tao Chen",
"Megha Tippur",
"Edward Adelson",
"Abhishek Gupta",
"Pulkit Agrawal",
"Sameer Pai",
"Tao Chen",
"Megha Tippur",
"Edward Adelson",
"Abhishek Gupta",
"Pulkit Agrawal"
] | We study the problem of object retrieval in scenarios where visual sensing is absent, object shapes are unknown beforehand and objects can move freely, like grabbing objects out of a drawer. Successful solutions require localizing free objects, identifying specific object instances, and then grasping the identified objects, only using touch feedback. Unlike vision, where cameras can observe the en... |
FingerSLAM: Closed-loop Unknown Object Localization and Reconstruction from Visuo-tactile Feedback | https://ieeexplore.ieee.org/document/10161489/ | [
"Jialiang Zhao",
"Maria Bauza",
"Edward H. Adelson",
"Jialiang Zhao",
"Maria Bauza",
"Edward H. Adelson"
] | In this paper, we address the problem of using visuo-tactile feedback for 6-DoF localization and 3D reconstruction of unknown in-hand objects. We propose FingerSLAM, a closed-loop factor graph-based pose estimator that combines local tactile sensing at finger-tip and global vision sensing from a wrist-mount camera. FingerSLAM is constructed with two constituent pose estimators: a multi-pass refine... |
Differential Dynamic Programming based Hybrid Manipulation Strategy for Dynamic Grasping | https://ieeexplore.ieee.org/document/10160817/ | [
"Cheng Zhou",
"Yanbo Long",
"Lei Shi",
"Longfei Zhao",
"Yu Zheng",
"Cheng Zhou",
"Yanbo Long",
"Lei Shi",
"Longfei Zhao",
"Yu Zheng"
] | To fully explore the potential of robots for dexterous manipulation, this paper presents a whole dynamic grasping process to achieve fluent grasping of a target object by the robot end-effector. The process starts from the phase of approaching the object over the phases of colliding with the object and letting it roll about the colliding point to the final phase of catching it by the palm or grasp... |
A Bioinspired Synthetic Nervous System Controller for Pick-and-Place Manipulation | https://ieeexplore.ieee.org/document/10161198/ | [
"Yanjun Li",
"Ravesh Sukhnandan",
"Jeffrey P. Gill",
"Hillel J. Chiel",
"Victoria Webster-Wood",
"Roger D. Quinn",
"Yanjun Li",
"Ravesh Sukhnandan",
"Jeffrey P. Gill",
"Hillel J. Chiel",
"Victoria Webster-Wood",
"Roger D. Quinn"
] | The Synthetic Nervous System (SNS) is a biologically inspired neural network (NN). Due to its capability of capturing complex mechanisms underlying neural computation, an SNS model is a candidate for building compact and interpretable NN controllers for robots. Previous work on SNSs has focused on applying the model to the control of legged robots and the design of functional subnetworks (FSNs) to... |
SDF-Based Graph Convolutional Q-Networks for Rearrangement of Multiple Objects | https://ieeexplore.ieee.org/document/10161394/ | [
"Hogun Kee",
"Minjae Kang",
"Dohyeong Kim",
"Jaegoo Choy",
"Songhwai Oh",
"Hogun Kee",
"Minjae Kang",
"Dohyeong Kim",
"Jaegoo Choy",
"Songhwai Oh"
] | In this paper, we propose a signed distance field (SDF)-based deep Q-learning framework for multi-object re-arrangement. Our method learns to rearrange objects with non-prehensile manipulation, e.g., pushing, in unstructured environments. To reliably estimate Q-values in various scenes, we train the Q-network using an SDF-based scene graph as the state-goal representation. To this end, we introduc... |
Towards Open-World Interactive Disambiguation for Robotic Grasping | https://ieeexplore.ieee.org/document/10161333/ | [
"Yuchen Mo",
"Hanbo Zhang",
"Tao Kong",
"Yuchen Mo",
"Hanbo Zhang",
"Tao Kong"
] | Language-based communications are essential in human-robot interaction, especially for the majority of non-expert users. In this paper, we present SeeAsk, an open-world interactive visual grounding system to grasp specified targets with ambiguous natural language instructions. The main contribution of SeeAsk is that it can robustly handle open-world scenes in terms of both open-set objects and ope... |
GenDexGrasp: Generalizable Dexterous Grasping | https://ieeexplore.ieee.org/document/10160667/ | [
"Puhao Li",
"Tengyu Liu",
"Yuyang Li",
"Yiran Geng",
"Yixin Zhu",
"Yaodong Yang",
"Siyuan Huang",
"Puhao Li",
"Tengyu Liu",
"Yuyang Li",
"Yiran Geng",
"Yixin Zhu",
"Yaodong Yang",
"Siyuan Huang"
] | Generating dexterous grasping has been a long-standing and challenging robotic task. Despite recent progress, existing methods primarily suffer from two issues. First, most prior art focuses on a specific type of robot hand, lacking generalizable capability of handling unseen ones. Second, prior arts oftentimes fail to rapidly generate diverse grasps with a high success rate. To jointly tackle the... |
Mechanical Intelligence for Prehensile In-Hand Manipulation of Spatial Trajectories | https://ieeexplore.ieee.org/document/10161170/ | [
"Qiujie Lu",
"Zhongxue Gan",
"Xinran Wang",
"Guochao Bai",
"Zhuang Zhang",
"Nicolas Rojas",
"Qiujie Lu",
"Zhongxue Gan",
"Xinran Wang",
"Guochao Bai",
"Zhuang Zhang",
"Nicolas Rojas"
] | The application of mechanical and other physical properties to the development of robotic systems that can easily adapt to changing external situations is known as mechanical intelligence. Following this concept, many robot hand designs can produce self-adaptive and versatile grasps with simple underactuated fingers and open-loop control, while mechanical- intelligent strategies for dexterous mani... |
Fast-Grasp'D: Dexterous Multi-finger Grasp Generation Through Differentiable Simulation | https://ieeexplore.ieee.org/document/10160314/ | [
"Dylan Turpin",
"Tao Zhong",
"Shutong Zhang",
"Guanglei Zhu",
"Eric Heiden",
"Miles Macklin",
"Stavros Tsogkas",
"Sven Dickinson",
"Animesh Garg",
"Dylan Turpin",
"Tao Zhong",
"Shutong Zhang",
"Guanglei Zhu",
"Eric Heiden",
"Miles Macklin",
"Stavros Tsogkas",
"Sven Dickinson",
"Animesh Garg"
] | Multi-finger grasping relies on high quality training data, which is hard to obtain: human data is hard to transfer and synthetic data relies on simplifying assumptions that reduce grasp quality. By making grasp simulation differentiable, and contact dynamics amenable to gradient-based optimization, we accelerate the search for high-quality grasps with fewer limiting assumptions. We present Grasp'... |
An Analysis of Unified Manipulation with Robot Arms and Dexterous Hands via Optimization-based Motion Synthesis | https://ieeexplore.ieee.org/document/10161325/ | [
"Vatsal V. Patel",
"Daniel Rakita",
"Aaron M. Dollar",
"Vatsal V. Patel",
"Daniel Rakita",
"Aaron M. Dollar"
] | Robot manipulation today generally focuses on motions exclusively with a robot arm or a dexterous hand, but usually not a combination of both. However, complex manipulation tasks can require coordinating arm and hand motions that leverage capabilities of both, much like the coordinated arm and hand motions carried out by humans to perform everyday tasks. In this work, we evaluate unified manipulat... |
Spherical Cubic Blends: $\mathcal{C}^{2}$-Continuous, Zero-Clamped, and Time-Optimized Interpolation of Quaternions | https://ieeexplore.ieee.org/document/10161346/ | [
"Jonas Wittmann",
"Lukas Cha",
"Marco Kappertz",
"Philipp Seiwald",
"Daniel J. Rixen",
"Jonas Wittmann",
"Lukas Cha",
"Marco Kappertz",
"Philipp Seiwald",
"Daniel J. Rixen"
] | Modern collaborative robotic applications require robot motions that are predictable for human coworkers. Therefore, trajectories often need to be planned in task space rather than configuration space ($\mathcal{C}$-space). While the interpolation of translations in Euclidean space is straightforward, the interpolation of rotations in $SO(3)$ is more complex. Most approaches originating from compu... |
Object Reconfiguration with Simulation-Derived Feasible Actions | https://ieeexplore.ieee.org/document/10160377/ | [
"Yiyuan Lee",
"Wil Thomason",
"Zachary Kingston",
"Lydia E. Kavraki",
"Yiyuan Lee",
"Wil Thomason",
"Zachary Kingston",
"Lydia E. Kavraki"
] | 3D object reconfiguration encompasses common robot manipulation tasks in which a set of objects must be moved through a series of physically feasible state changes into a desired final configuration. Object reconfiguration is challenging to solve in general, as it requires efficient reasoning about environment physics that determine action validity. This information is typically manually encoded i... |
CuRobo: Parallelized Collision-Free Robot Motion Generation | https://ieeexplore.ieee.org/document/10160765/ | [
"Balakumar Sundaralingam",
"Siva Kumar Sastry Hari",
"Adam Fishman",
"Caelan Garrett",
"Karl Van Wyk",
"Valts Blukis",
"Alexander Millane",
"Helen Oleynikova",
"Ankur Handa",
"Fabio Ramos",
"Nathan Ratliff",
"Dieter Fox",
"Balakumar Sundaralingam",
"Siva Kumar Sastry Hari",
"Adam Fishman",
"Caelan Garrett",
"Karl Van Wyk",
"Valts Blukis",
"Alexander Millane",
"Helen Oleynikova",
"Ankur Handa",
"Fabio Ramos",
"Nathan Ratliff",
"Dieter Fox"
] | This paper explores the problem of collision-free motion generation for manipulators by formulating it as a global motion optimization problem. We develop a parallel optimization technique to solve this problem and demonstrate its effectiveness on massively parallel GPUs. We show that combining simple optimization techniques with many parallel seeds leads to solving difficult motion generation pro... |
Allowing Safe Contact in Robotic Goal-Reaching: Planning and Tracking in Operational and Null Spaces | https://ieeexplore.ieee.org/document/10160649/ | [
"Xinghao Zhu",
"Wenzhao Lian",
"Bodi Yuan",
"C. Daniel Freeman",
"Masayoshi Tomizuka",
"Xinghao Zhu",
"Wenzhao Lian",
"Bodi Yuan",
"C. Daniel Freeman",
"Masayoshi Tomizuka"
] | In recent years, impressive results have been achieved in robotic manipulation. While many efforts focus on generating collision-free reference signals, few allow safe contact between the robot bodies and the environment. However, in human's daily manipulation, contact between arms and obstacles is prevalent and even necessary. This paper investigates the benefit of allowing safe contact during ro... |
Kinodynamic Rapidly-exploring Random Forest for Rearrangement-Based Nonprehensile Manipulation | https://ieeexplore.ieee.org/document/10161560/ | [
"Kejia Ren",
"Podshara Chanrungmaneekul",
"Lydia E. Kavraki",
"Kaiyu Hang",
"Kejia Ren",
"Podshara Chanrungmaneekul",
"Lydia E. Kavraki",
"Kaiyu Hang"
] | Rearrangement-based nonprehensile manipulation still remains as a challenging problem due to the high-dimensional problem space and the complex physical uncertainties it entails. We formulate this class of problems as a coupled problem of local rearrangement and global action optimization by incorporating free-space transit motions between constrained rearranging actions. We propose a forest-based... |
Trajectory Generation with Dynamic Programming for End-Effector Sway Damping of Forestry Machine | https://ieeexplore.ieee.org/document/10161232/ | [
"Iman Jebellat",
"Inna Sharf",
"Iman Jebellat",
"Inna Sharf"
] | When a robot end-effector is attached to the arm via passive joints, undesirable end-effector sway will occur. In a forestry crane, such as the log-loading or harvesting machine, this sway is problematic as it hinders the efficiency and also can harm the machine and environment. Here, we tackle the sway problem of the forestry forwarder by proposing a methodology for generating anti-sway trajector... |
Planning for Complex Non-prehensile Manipulation Among Movable Objects by Interleaving Multi-Agent Pathfinding and Physics-Based Simulation | https://ieeexplore.ieee.org/document/10161006/ | [
"Dhruv Mauria Saxena",
"Maxim Likhachev",
"Dhruv Mauria Saxena",
"Maxim Likhachev"
] | Real-world manipulation problems in heavy clutter require robots to reason about potential contacts with objects in the environment. We focus on pick-and-place style tasks to retrieve a target object from a shelf where some ‘movable’ objects must be rearranged in order to solve the task. In particular, our motivation is to allow the robot to reason over and consider non-prehensile rearrangement ac... |
Torque-Limited Manipulation Planning through Contact by Interleaving Graph Search and Trajectory Optimization | https://ieeexplore.ieee.org/document/10161297/ | [
"Ramkumar Natarajan",
"Garrison L.H. Johnston",
"Nabil Simaan",
"Maxim Likhachev",
"Howie Choset",
"Ramkumar Natarajan",
"Garrison L.H. Johnston",
"Nabil Simaan",
"Maxim Likhachev",
"Howie Choset"
] | Robots often have to perform manipulation tasks in close proximity to people (Fig 1). As such, it is desirable to use a robot arm that has limited joint torques so as to not injure the nearby person. Unfortunately, these limited torques then limit the payload capability of the arm. By using contact with the environment, robots can expand their reachable workspace that, otherwise, would be inaccess... |
FDLNet: Boosting Real-time Semantic Segmentation by Image-size Convolution via Frequency Domain Learning | https://ieeexplore.ieee.org/document/10161421/ | [
"Qingqing Yan",
"Shu Li",
"Chengju Liu",
"Ming Liu",
"Qijun Chen",
"Qingqing Yan",
"Shu Li",
"Chengju Liu",
"Ming Liu",
"Qijun Chen"
] | This paper proposes a novel real-time semantic segmentation network via frequency domain learning, called FDLNet, which revisits the segmentation task from two critical perspectives: spatial structure description and multilevel feature fusion. We first devise an image-size convolution (IS-Conv) as a global frequency-domain learning operator to capture long-range dependency in a single shot. To mod... |
SphNet: A Spherical Network for Semantic Pointcloud Segmentation | https://ieeexplore.ieee.org/document/10160412/ | [
"Lukas Bernreiter",
"Lionel Ott",
"Roland Siegwart",
"Cesar Cadena",
"Lukas Bernreiter",
"Lionel Ott",
"Roland Siegwart",
"Cesar Cadena"
] | Semantic segmentation for robotic systems can enable a wide range of applications, from self-driving cars and augmented reality systems to domestic robots. We argue that a spherical representation is a natural one for egocentric pointclouds. Thus, in this work, we present a novel framework exploiting such a representation of LiDAR pointclouds for the task of semantic segmentation. Our approach is ... |
SRI-Graph: A Novel Scene-Robot Interaction Graph for Robust Scene Understanding | https://ieeexplore.ieee.org/document/10161085/ | [
"Dong Yang",
"Xiao Xu",
"Mengchen Xiong",
"Edwin Babaians",
"Eckehard Steinbach",
"Dong Yang",
"Xiao Xu",
"Mengchen Xiong",
"Edwin Babaians",
"Eckehard Steinbach"
] | We propose a novel scene-robot interaction graph (SRI-Graph) that exploits the known position of a mobile manipulator for robust and accurate scene understanding. Compared to the state-of-the-art scene graph approaches, the proposed SRI-Graph captures not only the relationships between the objects, but also the relationships between the robot manipulator and objects with which it interacts. To imp... |
3D VSG: Long-term Semantic Scene Change Prediction through 3D Variable Scene Graphs | https://ieeexplore.ieee.org/document/10161212/ | [
"Samuel Looper",
"Javier Rodriguez-Puigvert",
"Roland Siegwart",
"Cesar Cadena",
"Lukas Schmid",
"Samuel Looper",
"Javier Rodriguez-Puigvert",
"Roland Siegwart",
"Cesar Cadena",
"Lukas Schmid"
] | Numerous applications require robots to operate in environments shared with other agents, such as humans or other robots. However, such shared scenes are typically subject to different kinds of long-term semantic scene changes. The ability to model and predict such changes is thus crucial for robot autonomy. In this work, we formalize the task of semantic scene variability estimation and identify ... |
Infrared Image Captioning with Wearable Device | https://ieeexplore.ieee.org/document/10160809/ | [
"Chenjun Gao",
"Yanzhi Dong",
"Xiaohu Yuan",
"Yifei Han",
"Huaping Liu",
"Chenjun Gao",
"Yanzhi Dong",
"Xiaohu Yuan",
"Yifei Han",
"Huaping Liu"
] | Wearable devices have garnered widespread attention as a mobile solution, and various intelligent modules based on wearable devices are increasingly being integrated. Additionally, image captioning is an important task in computer vision that maps images to text. Existing image captioning achievements are based on high-quality visible images. However, higher target complexity and insufficient ligh... |
External Camera-Based Mobile Robot Pose Estimation for Collaborative Perception with Smart Edge Sensors | https://ieeexplore.ieee.org/document/10160892/ | [
"Simon Bultmann",
"Raphael Memmesheimer",
"Sven Behnke",
"Simon Bultmann",
"Raphael Memmesheimer",
"Sven Behnke"
] | We present an approach for estimating a mobile robot's pose w.r.t. the allocentric coordinates of a network of static cameras using multi-view RGB images. The images are processed online, locally on smart edge sensors by deep neural networks to detect the robot and estimate 2D keypoints defined at distinctive positions of the 3D robot model. Robot keypoint detections are synchronized and fused on ... |
Feature-Realistic Neural Fusion for Real-Time, Open Set Scene Understanding | https://ieeexplore.ieee.org/document/10160800/ | [
"Kirill Mazur",
"Edgar Sucar",
"Andrew J. Davison",
"Kirill Mazur",
"Edgar Sucar",
"Andrew J. Davison"
] | General scene understanding for robotics requires flexible semantic representation, so that novel objects and structures which may not have been known at training time can be identified, segmented and grouped. We present an algorithm which fuses general learned features from a standard pre-trained network into a highly efficient 3D geometric neural field representation during real-time SLAM. The f... |
Deep Learning on Home Drone: Searching for the Optimal Architecture | https://ieeexplore.ieee.org/document/10160827/ | [
"Alaa Maalouf",
"Yotam Gurfinkel",
"Barak Diker",
"Oren Gal",
"Daniela Rus",
"Dan Feldman",
"Alaa Maalouf",
"Yotam Gurfinkel",
"Barak Diker",
"Oren Gal",
"Daniela Rus",
"Dan Feldman"
] | We suggest the first system that runs real-time semantic segmentation via deep learning on the weak microcomputer Raspberry Pi Zero v2 (whose price was $15) attached to a toy drone. In particular, since the Raspberry Pi weighs less than 16 grams, and its size is half of a credit card, we could easily attach it to the common commercial DJI Tello toy-drone (<$100, <90 grams, 98 $\times 92.5\times 41... |
Mask3D: Mask Transformer for 3D Semantic Instance Segmentation | https://ieeexplore.ieee.org/document/10160590/ | [
"Jonas Schult",
"Francis Engelmann",
"Alexander Hermans",
"Or Litany",
"Siyu Tang",
"Bastian Leibe",
"Jonas Schult",
"Francis Engelmann",
"Alexander Hermans",
"Or Litany",
"Siyu Tang",
"Bastian Leibe"
] | Modern 3D semantic instance segmentation approaches predominantly rely on specialized voting mechanisms followed by carefully designed geometric clustering techniques. Building on the successes of recent Transformer-based methods for object detection and image segmentation, we propose the first Transformer-based approach for 3D semantic instance segmentation. We show that we can leverage generic T... |
Detecting spatio-temporal Relations by Combining a Semantic Map with a Stream Processing Engine | https://ieeexplore.ieee.org/document/10160656/ | [
"Lennart Niecksch",
"Henning Deeken",
"Thomas Wiemann",
"Lennart Niecksch",
"Henning Deeken",
"Thomas Wiemann"
] | Changes in topological spatial relations of objects are often strong indicators for state transitions in the underlying processes they are involved in. While various aspects of semantic mapping have been extensively researched, the reasoning about the temporal development of spatial relations of instances is often neglected. This paper presents a concept to combine a semantic map with a stream pro... |
Cross-Modality Time-Variant Relation Learning for Generating Dynamic Scene Graphs | https://ieeexplore.ieee.org/document/10161478/ | [
"Jingyi Wang",
"Jinfa Huang",
"Can Zhang",
"Zhidong Deng",
"Jingyi Wang",
"Jinfa Huang",
"Can Zhang",
"Zhidong Deng"
] | Dynamic scene graphs generated from video clips could help enhance the semantic visual understanding in a wide range of challenging tasks such as environmental perception, autonomous navigation, and task planning of self-driving vehicles and mobile robots. In the process of temporal and spatial modeling during dynamic scene graph generation, it is particularly intractable to learn time-variant rel... |
CPSeg: Cluster-free Panoptic Segmentation of 3D LiDAR Point Clouds | https://ieeexplore.ieee.org/document/10160705/ | [
"Enxu Li",
"Ryan Razani",
"Yixuan Xu",
"Bingbing Liu",
"Enxu Li",
"Ryan Razani",
"Yixuan Xu",
"Bingbing Liu"
] | A fast and accurate panoptic segmentation system for LiDAR point clouds is crucial for autonomous driving vehicles to understand the surrounding objects and scenes. Existing approaches usually rely on proposals or clustering to segment foreground instances. As a result, they struggle to achieve real-time performance. In this paper, we propose a novel real-time end-to-end panoptic segmentation netw... |
A generic diffusion-based approach for 3D human pose prediction in the wild | https://ieeexplore.ieee.org/document/10160399/ | [
"Saeed Saadatnejad",
"Ali Rasekh",
"Mohammadreza Mofayezi",
"Yasamin Medghalchi",
"Sara Rajabzadeh",
"Taylor Mordan",
"Alexandre Alahi",
"Saeed Saadatnejad",
"Ali Rasekh",
"Mohammadreza Mofayezi",
"Yasamin Medghalchi",
"Sara Rajabzadeh",
"Taylor Mordan",
"Alexandre Alahi"
] | Predicting 3D human poses in real-world scenarios, also known as human pose forecasting, is inevitably subject to noisy inputs arising from inaccurate 3D pose estimations and occlusions. To address these challenges, we propose a diffusion-based approach that can predict given noisy observations. We frame the prediction task as a denoising problem, where both observation and prediction are consider... |
DifFAR: Differentiable Frequency-based Disentanglement for Aerial Video Action Recognition | https://ieeexplore.ieee.org/document/10160271/ | [
"Divya Kothandaraman",
"Ming Lin",
"Dinesh Manocha",
"Divya Kothandaraman",
"Ming Lin",
"Dinesh Manocha"
] | We present a learning algorithm, DifFAR, for human activity recognition in videos. Our approach is designed for UAV videos, which are mainly acquired from obliquely placed dynamic cameras that contain a human actor along with background motion. Typically, the human actors occupy less than one-tenth of the spatial resolution. DifFAR simultaneously harnesses the benefits of frequency domain represen... |
ANSEL Photobot: A Robot Event Photographer with Semantic Intelligence | https://ieeexplore.ieee.org/document/10161403/ | [
"Dmitriy Rivkin",
"Gregory Dudek",
"Nikhil Kakodkar",
"David Meger",
"Oliver Limoyo",
"Michael Jenkin",
"Xue Liu",
"Francois Hogan",
"Dmitriy Rivkin",
"Gregory Dudek",
"Nikhil Kakodkar",
"David Meger",
"Oliver Limoyo",
"Michael Jenkin",
"Xue Liu",
"Francois Hogan"
] | Our work examines the way in which large language models can be used for robotic planning and sampling in the context of automated photographic documentation. Specifically, we illustrate how to produce a photo-taking robot with an exceptional level of semantic awareness by leveraging recent advances in general purpose language (LM) and vision-language (VLM) models. Given a high-level description o... |
LODE: Locally Conditioned Eikonal Implicit Scene Completion from Sparse LiDAR | https://ieeexplore.ieee.org/document/10160552/ | [
"Pengfei Li",
"Ruowen Zhao",
"Yongliang Shi",
"Hao Zhao",
"Jirui Yuan",
"Guyue Zhou",
"Ya-Qin Zhang",
"Pengfei Li",
"Ruowen Zhao",
"Yongliang Shi",
"Hao Zhao",
"Jirui Yuan",
"Guyue Zhou",
"Ya-Qin Zhang"
] | Scene completion refers to obtaining dense scene representation from an incomplete perception of complex 3D scenes. This helps robots detect multi-scale obstacles and analyse object occlusions in scenarios such as autonomous driving. Recent advances show that implicit representation learning can be leveraged for continuous scene completion and achieved through physical constraints like Eikonal equ... |
Uncertainty-aware LiDAR Panoptic Segmentation | https://ieeexplore.ieee.org/document/10160355/ | [
"Kshitij Sirohi",
"Sajad Marvi",
"Daniel Büscher",
"Wolfram Burgard",
"Kshitij Sirohi",
"Sajad Marvi",
"Daniel Büscher",
"Wolfram Burgard"
] | Modern autonomous systems often rely on LiDAR scanners, in particular for autonomous driving scenarios. In this context, reliable scene understanding is indispensable. Conventional learning-based methods generally try to achieve maximum performance for this task, while neglecting a proper estimation of the associated uncertainties. In this work, we introduce a novel approach for solving the task o... |
E-VFIA: Event-Based Video Frame Interpolation with Attention | https://ieeexplore.ieee.org/document/10160276/ | [
"Onur Selim Kılıç",
"Ahmet Akman",
"A. Aydın Alatan",
"Onur Selim Kılıç",
"Ahmet Akman",
"A. Aydın Alatan"
] | Video frame interpolation (VFI) is a fundamental vision task that aims to synthesize several frames between two consecutive original video images. Most algorithms aim to accomplish VFI by using only keyframes, which is an ill-posed problem since the keyframes usually do not yield any accurate precision about the trajectories of the objects in the scene. On the other hand, event-based cameras provi... |
Edge-guided Multi-domain RGB-to-TIR image Translation for Training Vision Tasks with Challenging Labels | https://ieeexplore.ieee.org/document/10161210/ | [
"Dong–Guw Lee",
"Myung–Hwan Jeon",
"Younggun Cho",
"Ayoung Kim",
"Dong–Guw Lee",
"Myung–Hwan Jeon",
"Younggun Cho",
"Ayoung Kim"
] | The insufficient number of annotated thermal infrared (TIR) image datasets not only hinders TIR image-based deep learning networks to have comparable performances to that of RGB but it also limits the supervised learning of TIR image-based tasks with challenging labels. As a remedy, we propose a modified multidomain RGB to TIR image translation model focused on edge preservation to employ annotate... |
Weakly Supervised Referring Expression Grounding via Target-Guided Knowledge Distillation | https://ieeexplore.ieee.org/document/10161294/ | [
"Jinpeng Mi",
"Song Tang",
"Zhiyuan Ma",
"Dan Liu",
"Qingdu Li",
"Jianwei Zhang",
"Jinpeng Mi",
"Song Tang",
"Zhiyuan Ma",
"Dan Liu",
"Qingdu Li",
"Jianwei Zhang"
] | Weakly supervised referring expression grounding aims to train a model without the manual labels between image regions and referring expressions during the training phase. Current predominant models often adopt deep structures to reconstruct the region-expression correspondence. A crucial deficiency of the existing approaches lies in that these models neglect to exploit potential valuable informat... |
VQA-based Robotic State Recognition Optimized with Genetic Algorithm | https://ieeexplore.ieee.org/document/10160390/ | [
"Kento Kawaharazuka",
"Yoshiki Obinata",
"Naoaki Kanazawa",
"Kei Okada",
"Masayuki Inaba",
"Kento Kawaharazuka",
"Yoshiki Obinata",
"Naoaki Kanazawa",
"Kei Okada",
"Masayuki Inaba"
] | State recognition of objects and environment in robots has been conducted in various ways. In most cases, this is executed by processing point clouds, learning images with annotations, and using specialized sensors. In contrast, in this study, we propose a state recognition method that applies Visual Question Answering (VQA) in a Pre-Trained Vision-Language Model (PTVLM) trained from a large-scale... |
Center Feature Fusion: Selective Multi-Sensor Fusion of Center-based Objects | https://ieeexplore.ieee.org/document/10160616/ | [
"Philip Jacobson",
"Yiyang Zhou",
"Wei Zhan",
"Masayoshi Tomizuka",
"Ming C. Wu",
"Philip Jacobson",
"Yiyang Zhou",
"Wei Zhan",
"Masayoshi Tomizuka",
"Ming C. Wu"
] | Leveraging multi-modal fusion, especially between camera and LiDAR, has become essential for building accurate and robust 3D object detection systems for autonomous vehicles. Until recently, point decorating approaches, in which point clouds are augmented with camera features, have been the dominant approach in the field. However, these approaches fail to utilize the higher resolution images from ... |
Towards Robust Reference System for Autonomous Driving: Rethinking 3D MOT | https://ieeexplore.ieee.org/document/10160645/ | [
"Leichen Wang",
"Jiadi Zhang",
"Pei Cai",
"Xinrun Lil",
"Leichen Wang",
"Jiadi Zhang",
"Pei Cai",
"Xinrun Lil"
] | With the rapid development of autonomous driving, the need for auto-labeling reference systems is becoming increasingly urgent. 3D multiple object tracking (MOT) is one of the most critical components of the reference system. In this work, we reviewed and rethought the common failure sources and limitations of the SOTA 3D MOT methods. We propose a set of innovative 3D MOT post-processing modules a... |
LATITUDE: Robotic Global Localization with Truncated Dynamic Low-pass Filter in City-scale NeRF | https://ieeexplore.ieee.org/document/10161570/ | [
"Zhenxin Zhu",
"Yuantao Chen",
"Zirui Wu",
"Chao Hou",
"Yongliang Shi",
"Chuxuan Li",
"Pengfei Li",
"Hao Zhao",
"Guyue Zhou",
"Zhenxin Zhu",
"Yuantao Chen",
"Zirui Wu",
"Chao Hou",
"Yongliang Shi",
"Chuxuan Li",
"Pengfei Li",
"Hao Zhao",
"Guyue Zhou"
] | Neural Radiance Fields (NeRFs) have made great success in representing complex 3D scenes with high-resolution details and efficient memory. Nevertheless, current NeRF - based pose estimators have no initial pose prediction and are prone to local optima during optimization. In this paper, we present LATITUDE: Global Localization with Truncated Dynamic Low-pass Filter, which introduces a two-stage l... |
4DRadarSLAM: A 4D Imaging Radar SLAM System for Large-scale Environments based on Pose Graph Optimization | https://ieeexplore.ieee.org/document/10160670/ | [
"Jun Zhang",
"Huayang Zhuge",
"Zhenyu Wu",
"Guohao Peng",
"Mingxing Wen",
"Yiyao Liu",
"Danwei Wang",
"Jun Zhang",
"Huayang Zhuge",
"Zhenyu Wu",
"Guohao Peng",
"Mingxing Wen",
"Yiyao Liu",
"Danwei Wang"
] | LiDAR-based SLAM may easily fail in adverse weathers (e.g., rain, snow, smoke, fog), while mmWave Radar remains unaffected. However, current researches are primarily focused on 2D $(x,y)$ or 3D ($x, y$, doppler) Radar and 3D LiDAR, while limited work can be found for 4D Radar ($x, y, z$, doppler). As a new entrant to the market with unique characteristics, 4D Radar outputs 3D point cloud with adde... |
A Unified BEV Model for Joint Learning of 3D Local Features and Overlap Estimation | https://ieeexplore.ieee.org/document/10160492/ | [
"Lin Li",
"Wendong Ding",
"Yongkun Wen",
"Yufei Liang",
"Yong Liu",
"Guowei Wan",
"Lin Li",
"Wendong Ding",
"Yongkun Wen",
"Yufei Liang",
"Yong Liu",
"Guowei Wan"
] | Pairwise point cloud registration is a critical task for many applications, which heavily depends on finding correct correspondences from the two point clouds. However, the low overlap between input point clouds causes the registration to fail easily, leading to mistaken overlapping and mismatched correspondences, especially in scenes where non-overlapping regions contain similar structures. In th... |
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