51 citations · 118 across the 11 of their papers we have counts for
12 papers
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…
DARE: AI-based Diver Action Recognition System using Multi-Channel CNNs for AUV Supervision
Jing Yang, James P. Wilson, Shalabh Gupta
With the growth of sensing, control and robotic technologies, autonomous underwater vehicles (AUVs) have become useful assistants to human divers for performing various underwater…
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…
POSE.R: Prediction-based Opportunistic Sensing for Resilient and Efficient Sensor Networks
James Z. Hare, Junnan Song, Shalabh Gupta +1
The paper presents a distributed algorithm, called Prediction-based Opportunistic Sensing for Resilient and Efficient Sensor Networks (POSE.R), where the sensor nodes utilize predi…
Rapid Path Planning for Dubins Vehicles under Environmental Currents
Khushboo Mittal, Junnan Song, Shalabh Gupta +1
This paper presents a rapid (real time) solution to the minimum-time path planning problem for Dubins vehicles under environmental currents (wind or ocean currents). Real-time solu…
CARE: Cooperative Autonomy for Resilience and Efficiency of Robot Teams for Complete Coverage of Unknown Environments under Robot Failures
Junnan Song, Shalabh Gupta
This paper addresses the problem of Multi-robot Coverage Path Planning (MCPP) for unknown environments in the presence of robot failures. Unexpected robot failures can seriously de…