Marco Herrera

Evaluating Deep Actor–Critic Methods for Path Planning of Mobile Manipulators Under Wheel–Terrain Interaction

Reinforcement learning (RL) has become an effective paradigm for enabling autonomous robots to acquire navigation policies directly from interaction with complex and uncertain environments. Nevertheless, autonomous path planning for Skid-Steer Mobile Manipulators (SSMMs) remains a challenging problem because it require...