Advanced Sensing and Control Technologies for Autonomous Robots

<p class=ql-align-justify>This Reprint compiles cutting-edge research on sensor-driven autonomy and adaptive control strategies for robotic systems operating in dynamic industrial and unstructured environments. It highlights innovations in robust control architectures such as model-free adaptive control and fault-tolerant MPC frameworks alongside advancements in perception technologies such as NeoSLAM and TSG-SLAM for dynamic scene navigation. The Reprint's contributions emphasize the synergy of LiDAR-vision-inertial sensor fusion with intelligent decision-making algorithms such as SAC-LSTM path planning while exploring novel paradigms such as artificially empathetic swarm control. By bridging theoretical rigor with industrial implementation this Reprint provides a vital resource for researchers and engineers advancing resilient robotic autonomy through adaptive control real-time perception and multi-agent coordination in logistics construction and human-robot collaboration.</p><p></p>