Autonomously Reconfigurable Robot Coupled with Intelligent Vision and Control System for Rapid Runtime Adaptation

The widespread integration of robotic technology across diverse sector’s necessitates solutions that embody both adaptability and speed. However, existing systems often exhibit a trade-off between these attributes, lacking swift adaptability. This paper introduces a novel self-reconfiguration system that addresses this challenge. Employing a scissor mechanism for rapid adjustment and an intelligent binocular vision driven by computer vision and reinforcement learning algorithms, the proposed system facilitates swift reconfiguration while effectively managing workload. Real-time perception and understanding of the surroundings enable the robot to promptly identify optimal dimensions and adjust its configuration accordingly. This capability empowers the robot to rapidly respond to new tasks without manual intervention, thereby augmenting its versatility and agility. Experimental validation demonstrates the system’s adeptness in navigating passages of varying widths in under a second, underscoring the efficacy of our approach in training the robot to adeptly adapt to diverse environmental conditions.