Variable admittance control algorithm for robots based on task-space boundary constraints

To address the challenges of compliance and safety in robot direct teaching within a constrained task space, this paper proposes a variable admittance control algorithm based on task-space boundary constraints. First, the forward kinematics of a SCARA robot are solved using the exponential product method, and its operational workspace is determined via the Monte Carlo method, within which the teaching task space is defined. A virtual repulsive force, correlated with the distance to the boundary, is introduced when the robot end-effector approaches the task-space limits. The core of the proposed algorithm lies in dynamically adjusting the virtual inertia and damping parameters of the admittance controller based on the combined input of this virtual force and the human teaching force. Specifically, as the resultant force decreases near the boundary, the damping is increased to achieve smooth deceleration and avoid impulsive stops. Comparative simulations and experiments against a fixed-parameter admittance control strategy were conducted to validate the algorithm's performance. The results demonstrate that, unlike the conventional method which tends to cause abrupt stops at the boundary, our approach enables the robot to decelerate progressively and stop compliantly. The steady-state positioning error at the boundary remains within 6 mm, without overshoot or oscillation, significantly enhancing the safety and interactive compliance of the direct teaching operation.