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…
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…
Multi-CAP: A Multi-Robot Connectivity-Aware Hierarchical Coverage Path Planning Algorithm for Unknown Environments
Zongyuan Shen, Burhanuddin Shirose, Prasanna Sriganesh +3
Efficient coordination of multiple robots for coverage of large, unknown environments is a significant challenge that involves minimizing the total coverage path length while reduc…
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…