Wrench-Aware Admittance Control for Unknown-Payload Manipulation

2026-04-21

AI Summary

This work addresses the challenge posed by unknown payloads—particularly those with center-of-mass offsets from the tool center point—which introduce additional torques during compliant manipulation, leading to increased tracking errors and reduced handling accuracy. The paper proposes a torque-aware admittance control framework that explicitly models and compensates for payload-induced torques in real time. By leveraging the wrist-mounted force/torque sensor of a UR5e robot, the method online estimates both the payload mass and its center-of-mass offset, and applies three-axis translational excitation during manipulation to mitigate force disturbances. Experimental results demonstrate that the approach significantly enhances the precision and stability of tasks involving unknown payload transport, placement, and stacking, while preserving desirable compliance characteristics.

Technology Category

• Intelligent Robots: Manipulation
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Planning, Routing, and Scheduling: Activity and Plan Recognition

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

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.

Problem

• unknown payload
• wrench estimation
• compliant manipulation
• center of mass offset
• admittance control

Innovation

• wrench-aware admittance control
• unknown-payload manipulation
• center of mass estimation
• force-torque sensing
• compliant robotic manipulation