Confined Space Navigation via Deep Reinforcement Learning
Published in , 2023
Trained a robot to safely enter tight spaces like elevators using Deep RL. Presented at UR 2023.
Posts by Collection
projects
Multi-Robot System with TurtleBot4 & ROS 2
Published in , 2024
Built a real-world testing platform using TurtleBot4 robots and ROS2 for multi-robot navigation experiments.
Human Demonstration Collection in PyBullet
Published in , 2024
Developed a PyBullet-based interactive environment to collect human demonstrations for robot navigation learning.
Multi-Robot Path Planning with Isaac Sim
Published in , 2024
Developed a dynamic 3D simulation in Isaac Sim to test multi-robot scalability and collision-free path planning.
publications
Room for me?: Mobile Navigation for Entering a Confined Space Using Deep Reinforcement Learning
Published in Int. Conf. on Ubiquitous Robots (UR), IEEE, 2023, 2023
Inspired by challenges in elevator navigation, this work uses deep reinforcement learning to enable robots to safely enter confined spaces.
Safe Interval RRT* for Scalable Multi-Robot Path Planning in Continuous Space
Published in Under review, 2024
This paper proposes Safe Interval RRT*, a scalable algorithm for multi-robot path planning in continuous spaces.
Safe Interval RRT* for Scalable Multi-Robot Path Planning in Continuous Space
Published in Under revision, 2025
This paper proposes Safe Interval RRT*, a scalable algorithm for multi-robot path planning in continuous spaces.
Escaping Local Minima: Hybrid Artificial Potential Field with Wall-Follower for Decentralized Multi-Robot Navigation
Published in Int. Conf. on Robotics and Automation (ICRA), 2025, 2025
We introduce a hybrid navigation algorithm that switches between Artificial Potential Field (APF) and Wall-Following (WF) to overcome local minima in decentralized multi-robot systems.