12 papers · 1 filter
TRACE: Coverage Path Planning for Unknown Environments Using Hierarchical Coverage Tree
Zongyuan Shen, Haodong Liu, Gao Wang +6
This paper presents a novel online coverage path planning (CPP) algorithm, called TRACE, for real-time coverage of unknown environments. TRACE is built upon a hierarchical coverage…
Learning-Based Motion Planning for Dynamic Environments: From Foundational Algorithms to Emerging Paradigms
Zongyuan Shen, Shalabh Gupta, Shancheng Zhao +7
Motion planning in dynamic environments is a fundamental problem in robotics, aiming to generate safe and efficient paths, trajectories, or control actions in the presence of movin…
Coverage Path Planning: Classical Foundations, Recent Advances, and Future Directions
Zongyuan Shen, Shalabh Gupta, Shancheng Zhao +6
Coverage path planning (CPP) is a fundamental problem in robot motion planning, whose aim is to produce robot trajectories that provide complete coverage of target workspaces while…
EgoInfinity: A Web-Scale 4D Hand-Object Interaction Data Engine for Any-View Robot Retargeting and Video-to-Action Robot Learning
Gaotian Wang, Kejia Ren, Andrew Morgan +4
Internet videos constitute the largest reservoir of embodied human manipulation knowledge, yet converting arbitrary RGB footage into actionable robot training data remains a major…
Motion Planning in Dynamic Environments: A Survey from Classical to Modern Methods
Zongyuan Shen, Yaming Ou, Shalabh Gupta +6
Motion planning in dynamic environments requires robots to continuously adapt their paths in response to environmental changes for safe and uninterrupted navigation. While many sur…
Zero-Shot Sim-to-Real Robot Learning: A Dexterous Manipulation Study on Reactive Catching
Kejia Ren, Gaotian Wang, Andrew S. Morgan +1
Dexterous manipulation is physics-intensive and highly sensitive to modeling errors and perception noise, making sim-to-real transfer prohibitively challenging. Domain randomizatio…
ManiDreams: An Open-Source Library for Robust Object Manipulation via Uncertainty-aware Task-specific Intuitive Physics
Gaotian Wang, Kejia Ren, Andrew S. Morgan +1
Dynamics models, whether simulators or learned world models, have long been central to robotic manipulation, but most focus on minimizing prediction error rather than confronting a…
rt-RISeg: Real-Time Model-Free Robot Interactive Segmentation for Active Instance-Level Object Understanding
Howard H. Qian, Yiting Chen, Gaotian Wang +2
Successful execution of dexterous robotic manipulation tasks in new environments, such as grasping, depends on the ability to proficiently segment unseen objects from the backgroun…
Collision-Inclusive Manipulation Planning for Occluded Object Grasping via Compliant Robot Motions
Kejia Ren, Gaotian Wang, Andrew S. Morgan +1
Robotic manipulation research has investigated contact-rich problems and strategies that require robots to intentionally collide with their environment, to accomplish tasks that ca…
Caging in Time: A Framework for Robust Object Manipulation under Uncertainties and Limited Robot Perception
Gaotian Wang, Kejia Ren, Andrew S. Morgan +1
Real-world object manipulation has been commonly challenged by physical uncertainties and perception limitations. Being an effective strategy, while caging configuration-based mani…
Object-Centric Kinodynamic Planning for Nonprehensile Robot Rearrangement Manipulation
Kejia Ren, Gaotian Wang, Andrew S. Morgan +2
Nonprehensile actions such as pushing are crucial for addressing multi-object rearrangement problems. Many traditional methods generate robot-centric actions, which differ from int…
UNO Push: Unified Nonprehensile Object Pushing via Non-Parametric Estimation and Model Predictive Control
Gaotian Wang, Kejia Ren, Kaiyu Hang
Nonprehensile manipulation through precise pushing is an essential skill that has been commonly challenged by perception and physical uncertainties, such as those associated with c…