Abstract
Handling objects with unknown or changing masses is a common challenge in robotics, often leading to errors or instability if the control system cannot adapt in real-time. In this paper, we present a novel approach that enables a six-degrees-of-freedom robotic manipulator to reliably follow waypoints while automatically estimating and compensating for unknown payload weight. Our method integrates an admittance control framework with a mass estimator, allowing the robot to dynamically update an excitation force to compensate for the payload mass. This strategy mitigates end-effector sagging and preserves stability when handling objects of unknown weights. We experimentally validated our approach in a challenging pick-and-place task on a shelf with a crossbar, improved accuracy in reaching waypoints and compliant motion compared to a baseline admittance-control scheme. By safely accommodating unknown payloads, our work enhances flexibility in robotic automation and represents a significant step forward in adaptive control for uncertain environments.
Abstract (translated)
处理未知或变化质量的物体是机器人技术中的一个常见挑战，如果控制系统不能实时适应，则会导致错误或不稳定。本文提出了一种新颖的方法，使六自由度的机械臂能够在跟随路径点时可靠地自动估算并补偿未知负载重量。我们的方法将顺应性控制框架与质量估计算法相结合，允许机器人动态更新激励力以补偿负载质量。这种策略减少了末端执行器下垂，并在处理未知重量物体时保持稳定性。 我们在一个具有横杆的货架上进行了一项具有挑战性的拾取和放置任务的实验验证，结果表明我们的方法比基线顺应性控制方案在到达路径点和顺从运动方面更为准确。通过安全地适应未知负载，我们的工作增强了机器人自动化中的灵活性，并在不确定环境中自适应控制领域中迈出了重要一步。
URL
https://arxiv.org/abs/2504.16224
