Adaptive safety-critical control using a variable task energy tank for collaborative robot tasks under dynamic environments

Abstract

Collaborative robots are widely used in interaction tasks due to their low cost and high operational flexibility. However, compared to industrial robots, they have lower joint stiffness and are more sensitive to external environments, leading to larger motion tracking errors. Therefore, in interaction tasks within complex dynamic environments, such as wiping tasks with unexpected collision disturbances and drilling tasks with material property changes, maintaining the stability of the robot's motion velocity is crucial for improving task performance. To address these concerns, a comprehensive passive safety control framework is proposed in this work. The framework ensures system stability while imposing consistently constraints on non-passive power of the controller, resulting in high performance in the presence of external disturbances and material property changes. This is achieved by combining the Variable Energy Tank with the Adaptive Control Barrier Function method. On this basis, two key parameter design strategies of the framework are proposed, including a variable reference energy boundary strategy and an adaptive conservative factor strategy. The effectiveness of the proposed method is validated by real-world experiments involving wiping and drilling.