A Variable Admittance Control Strategy for Robotic Constraints Avoidance Based on Virtual Fixtures

Abstract

Robotic constraints avoidance is important for collaborative robots to achieve safe interactions with operators. However, it is difficult to simultaneously handle the various constraints which are described in different space. In this research, a control framework is proposed for solving the problem of robotic constraints avoidance based on virtual fixtures and adaptive admittance control. Specifically, different constraints are evaluated by geometric distances and redescribed as potential fields in Cartesian space. Then, a virtual repulsive force is generated with considering operator’s intention to drive robot away from the constraint areas. Furtherly, an adaptive admittance controller is constructed to ensure the stability of system. Simulations are conducted on AUBO I5 robots under three scenarios and the effectiveness of the proposed framework in handling robot’s self-collision, workspace collision, configuration singularity and joint-limit violation is verified.