Terrestrial Mobile Robot

Terrestrial mobile robots are autonomous systems designed for navigation and manipulation in diverse environments, with research focusing on improving their efficiency, robustness, and adaptability. Current efforts emphasize developing advanced control algorithms, particularly deep reinforcement learning (including DQN and DDQN variants) and hybrid approaches combining classical planning with neural networks, to enable mapless navigation and precise manipulation, even with limited sensing. These advancements are crucial for expanding the capabilities of robots in various applications, from industrial automation and search and rescue to exploration and environmental monitoring.