8 papers
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…
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…
PECMAN: Perception-enabled Collaborative Multi-Agent Navigation in Unknown Environments
Tianchonghui Fang, Shaunak Roy, Shalabh Gupta
Most path planners assume fully known, static environments, assumptions that fail when robots navigate in dynamic and partially observable environments. SMART-3D addresses these is…
C*: A Coverage Path Planning Algorithm for Unknown Environments using Rapidly Covering Graphs
Zongyuan Shen, James P. Wilson, Shalabh Gupta
The paper presents a novel sample-based algorithm, called C*, for real-time coverage path planning (CPP) of unknown environments. C* is built upon the concept of a Rapidly Covering…
SMART-3D: Three-Dimensional Self-Morphing Adaptive Replanning Tree
Priyanshu Agrawal, Shalabh Gupta, Zongyuan Shen
This paper presents SMART-3D, an extension of the SMART algorithm to 3D environments. SMART-3D is a tree-based adaptive replanning algorithm for dynamic environments with fast movi…