20 citations · 57 across the 16 of their papers we have counts for
17 papers
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…
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…
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…
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…
An Underwater, Fault-Tolerant, Laser-Aided Robotic Multi-Modal Dense SLAM System for Continuous Underwater In-Situ Observation
Yaming Ou, Junfeng Fan, Chao Zhou +5
Existing underwater SLAM systems are difficult to work effectively in texture-sparse and geometrically degraded underwater environments, resulting in intermittent tracking and spar…
CAP: A Connectivity-Aware Hierarchical Coverage Path Planning Algorithm for Unknown Environments using Coverage Guidance Graph
Zongyuan Shen, Burhanuddin Shirose, Prasanna Sriganesh +1
Efficient coverage of unknown environments requires robots to adapt their paths in real time based on on-board sensor data. In this paper, we introduce CAP, a connectivity-aware hi…
SMART: Self-Morphing Adaptive Replanning Tree
Zongyuan Shen, James P. Wilson, Shalabh Gupta +1
The paper presents an algorithm, called Self-Morphing Adaptive Replanning Tree (SMART), that facilitates fast replanning in dynamic environments. SMART performs risk based tree-pru…
SMARRT: Self-Repairing Motion-Reactive Anytime RRT for Dynamic Environments
Zongyuan Shen, James Wilson, Ryan Harvey +1
This paper addresses the fast replanning problem in dynamic environments with moving obstacles. Since for randomly moving obstacles the future states are unpredictable, the propose…
CPPNet: A Coverage Path Planning Network
Zongyuan Shen, Palash Agrawal, James P. Wilson +2
This paper presents a deep-learning based CPP algorithm, called Coverage Path Planning Network (CPPNet). CPPNet is built using a convolutional neural network (CNN) whose input is a…
A Non-uniform Sampling Approach for Fast and Efficient Path Planning
James P. Wilson, Zongyuan Shen, Shalabh Gupta
In this paper, we develop a non-uniform sampling approach for fast and efficient path planning of autonomous vehicles. The approach uses a novel non-uniform partitioning scheme tha…
MRRT: Multiple Rapidly-Exploring Random Trees for Fast Online Replanning in Dynamic Environments
Zongyuan Shen, James P. Wilson, Ryan Harvey +1
This paper presents a novel algorithm, called MRRT, which uses multiple rapidly-exploring random trees for fast online replanning of autonomous vehicles in dynamic environments wit…
CT-CPP: Coverage Path Planning for 3D Terrain Reconstruction Using Dynamic Coverage Trees
Zongyuan Shen, Junnan Song, Khushboo Mittal +1
This letter addresses the 3D coverage path planning (CPP) problem for terrain reconstruction of unknown obstacle rich environments. Due to sensing limitations, the proposed method,…
T-Lite: A Fast Time-Risk Optimal Motion Planning Algorithm for Multi-Speed Autonomous Vehicles
James P. Wilson, Zongyuan Shen, Shalabh Gupta +1
In this paper, we develop a new algorithm, called T-Lite, that enables fast time-risk optimal motion planning for variable-speed autonomous vehicles. The T-Lite…
+: An Online Coverage Path Planning Algorithm for Energy-constrained Autonomous Vehicles
Zongyuan Shen, James P. Wilson, Shalabh Gupta
This paper presents a novel algorithm, called +, for online coverage path planning of unknown environments using energy-constrained autonomous vehicles. Due to limited battery…