Human–Robot Interaction Control With Constrained Space and Compliant Behavior: Integral Barrier Lyapunov Function Approach

This article presents a novel control method based on an integral barrier Lyapunov function (IBLF) to facilitate human-compliant physical interaction in constrained spaces. The proposed control approach prioritizes the comfort and safety of muscle strength rehabilitation training. At the planning level, a trajectory deformation algorithm combined with a saturation function is introduced to generate a desired trajectory that respects spatial constraints while allowing the robot to adapt to human movement. At the actuation level, an IBLF-based control strategy with a disturbance observer is employed to address trajectory tracking challenges and robotic task space constraints. The disturbance observer estimates and compensates for external disturbances affecting the robot’s actuators, thereby enhancing tracking accuracy. Meanwhile, the IBLF framework shapes the robot’s movement boundaries to ensure interaction safety. Using Lyapunov stability theory, we prove that all states of the closed-loop system remain semiglobally uniformly ultimately bounded, ensuring system reliability. The effectiveness of the proposed approach is validated through a series of experiments conducted on an upper limb exoskeleton robotic system.