Constructive Extension of Deep Reinforcement Learning Network for Multi-Robot Obstacle Avoidance and Navigation in Generalized Map Environment
This research aims to integrate constructive neural networks and virtual robot placement strategy to achieve obstacle avoidance and navigation for multiple robots in a generalized map environment. Deep reinforcement learning theory is applied to design neural networks, which are trained in free space to improve the performance of the dual robot system in obstacle avoidance …