M. Kalaimani

Real-time obstacle avoidance in mobile robots using deep reinforcement learning

The proposed Proximal Policy Optimization-based deep reinforcement learning approach for real-time obstacle avoidance for mobile robots is a successful and computationally feasible solution to real-time robotic navigation in dynamic environments.