发表机构
University of Cambridge（剑桥大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出六种虚拟模型控制设计方法，用于力控机械臂在障碍和不确定环境下完成到达任务，并通过8自由度人形机器人实验验证其有效性。
AI 中文摘要
虚拟模型控制（VMC）是一种在复杂不确定环境中为力控机器人设计控制器的方法。尽管该方法过去主要被研究用于腿式机器人运动，但它可以更普遍地适用于其他类型的机器人系统。本文研究了力控机械臂在执行到达任务时的VMC框架。我们提出了六种不同的虚拟模型设计方法，以实现在存在障碍物和不确定性的环境中完成到达任务。一个8自由度的力控人形机器人被用于在真实世界中验证所提出的方法。我们进行了三个实验来测试VMC控制器在可预测性、对外部力的敏感性以及对已知和未知障碍物的适应性方面的性能。实验分析表明，尽管所提出的方法需要牺牲精度和轨迹最优性，但它使我们能够以直观且可扩展的方式在不确定性下设计复杂的到达运动。
英文摘要
Virtual Model Control (VMC) is an approach to design a controller for force-controlled robots in complex uncertain environments. While this method was primarily investigated for legged robot locomotion in the past, it can be more generally applicable to other types of robotic systems. This paper investigates the VMC framework for reaching tasks in a force-controlled robotic arm. We propose six different approaches to designing virtual models in order to achieve reaching tasks in environments with obstacles and uncertainties. A force-controlled 8 degree-of-freedom humanoid robot was used to validate the proposed approach in the real world. We conducted three experiments to test the performance of VMC controllers in terms of predictability, sensitivity to external force, and adaptability against known and unknown obstacles. Experimental analyses show that, even though the proposed approach needs to sacrifice accuracy and trajectory optimality, it enables us to design complex reaching motions under uncertainties, in an intuitive and extendable manner.
Journal refY. Zhang, D. Larby, F. Iida and F. Forni, "Virtual model control for compliant reaching under uncertainties," Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst. (IROS), 2024, pp. 795-801, doi: 10.1109/IROS58592.2024.10801592
