Unified humanoid manipulation of an object of unknown mass properties and friction based on online constraint estimation

Shunichi Nozawa, Masaki Murooka, Shintaro Noda, Kunio Kojima, Yuta Kojio, Youhei Kakiuchi, K. Okada, M. Inaba
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引用次数: 1

Abstract

In the case of object manipulation, a humanoid robot should consider the two-body problem between the object and the robot. To achieve this, the motion planner and the controller must satisfy constraints among the robot, the object, and environments. In addition, the objecfs properties such as mass properties and friction are not known a priori and the robot must obtain this information based on sensor feedback. In this paper, we propose a method for uniform humanoid manipulation of an unknown object by estimating objectenvironment constraints based on changes in the robofs force sensor measurements. The proposed method supports various types of manipulation (lifting, pushing, pivoting), various robot contacts (single-armed, dual-armed, full-body), multi-robot cooperative manipulation, and motion on a movable object. We evaluate the proposed method through experiments involving manipulation of large and heavy objects using life-sized real robots.
基于在线约束估计的未知质量和摩擦物体的统一仿人操纵
人形机器人在操纵物体时,应考虑物体与机器人之间的二体问题。为了实现这一目标,运动规划器和控制器必须满足机器人、物体和环境之间的约束。此外,物体的质量和摩擦力等属性是未知的,机器人必须根据传感器的反馈来获取这些信息。在本文中,我们提出了一种基于机器人力传感器测量值的变化来估计物体环境约束的方法,以实现对未知物体的均匀人形操纵。所提出的方法支持各种类型的操作(提升,推动,旋转),各种机器人接触(单臂,双臂,全身),多机器人协作操作以及在可移动物体上的运动。我们通过使用真人大小的真实机器人操纵大型和重型物体的实验来评估所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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