3 citations · 5 across the 11 of their papers we have counts for
11 papers
HDPlanner: Advancing Autonomous Deployments in Unknown Environments through Hierarchical Decision Networks
Jingsong Liang, Yuhong Cao, Yixiao Ma +2
In this paper, we introduce HDPlanner, a deep reinforcement learning (DRL) based framework designed to tackle two core and challenging tasks for mobile robots: autonomous explorati…
Social Behavior as a Key to Learning-based Multi-Agent Pathfinding Dilemmas
Chengyang He, Tanishq Duhan, Parth Tulsyan +2
The Multi-agent Path Finding (MAPF) problem involves finding collision-free paths for a team of agents in a known, static environment, with important applications in warehouse auto…
Privileged Reinforcement and Communication Learning for Distributed, Bandwidth-limited Multi-robot Exploration
Yixiao Ma, Jingsong Liang, Yuhong Cao +2
Communication bandwidth is an important consideration in multi-robot exploration, where information exchange among robots is critical. While existing methods typically aim to reduc…
STAR: Swarm Technology for Aerial Robotics Research
Jimmy Chiun, Yan Rui Tan, Yuhong Cao +2
In recent years, the field of aerial robotics has witnessed significant progress, finding applications in diverse domains, including post-disaster search and rescue operations. Des…
Learning-based Hierarchical Control: Emulating the Central Nervous System for Bio-Inspired Legged Robot Locomotion
Ge Sun, Milad Shafiee, Peizhuo Li +3
Animals possess a remarkable ability to navigate challenging terrains, achieved through the interplay of various pathways between the brain, central pattern generators (CPGs) in th…
Deep Reinforcement Learning-based Large-scale Robot Exploration
Yuhong Cao, Rui Zhao, Yizhuo Wang +2
In this work, we propose a deep reinforcement learning (DRL) based reactive planner to solve large-scale Lidar-based autonomous robot exploration problems in 2D action space. Our D…