Autonomous Framework

Autonomous frameworks encompass the design and implementation of systems enabling robots to perform complex tasks independently, ranging from fruit harvesting and lab equipment operation to disaster response and industrial assembly. Current research emphasizes integrating advanced perception (e.g., computer vision, LiDAR) with robust control algorithms (including reinforcement learning and force-impedance control) to achieve reliable autonomous behavior in diverse and unpredictable environments. This field is significant for advancing robotics capabilities across various sectors, from agriculture and manufacturing to healthcare and infrastructure management, by improving efficiency, safety, and operational flexibility.