Depth-based obstacle avoidance through deep reinforcement learning

• Main Authors: Wu, Keyu, Mahdi Abolfazli Esfahani, Yuan, Shenghai, Wang, Han
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: Engineering::Electrical and electronic engineering; Deep Reinforcement Learning; Obstacle Avoidance
• Online Access: https://hdl.handle.net/10356/142309
• Institution: Nanyang Technological University

Obstacle avoidance is an indispensable technique for mobile robots to maneuver safely without collision. In this paper, we propose an end-to-end deep neural network to derive control commands directly from the raw depth images using deep reinforcement learning. The convolutional neural networks are...