Wrench-Aware Admittance Control for Unknown-Payload Manipulation
For robotic manipulation tasks with unknown payloads, this work addresses the practical problem of unintended compliant motion and reduced accuracy by providing a method that estimates payload properties without requiring prior knowledge.
The paper presents a wrench-aware admittance control framework for unknown-payload pick-and-place that estimates payload mass and center-of-mass offset using force-torque measurements, reducing unintended motion and improving transport accuracy. Experiments on a UR5e robot show improved placement performance compared to uncorrected methods while preserving compliance.
Unknown payloads can strongly affect compliant robotic manipulation, especially when the payload center of mass is not aligned with the tool center point. In this case, the payload generates an offset wrench at the robot wrist. During motion, this wrench is not only related to payload weight, but also to payload inertia. If it is not modeled, the compliant controller can interpret it as an external interaction wrench, which causes unintended compliant motion, larger tracking error, and reduced transport accuracy. This paper presents a wrench-aware admittance control framework for unknown-payload pick-and-place using a UR5e robot. The method uses force-torque measurements in two different roles. First, a three-axis translational excitation term is used to reduce payload-induced force effects during transport without making the robot excessively stiff. Second, after grasping, the controller first estimates payload mass for transport compensation and then estimates the payload CoM offset relative to the TCP using wrist force-torque measurements collected during the subsequent translational motion. This helps improve object placement and stacking behavior. Experimental results show improved transport and placement performance compared with uncorrected placement while preserving compliant motion.