论文标题

我可以举起吗?人形机器人的推理,说明具有未知物理特性的重盒的可行性

Can I lift it? Humanoid robot reasoning about the feasibility of lifting a heavy box with unknown physical properties

论文作者

Han, Yuanfeng, Li, Ruixin, Chirikjian, Gregory S.

论文摘要

如果机器人不可行,机器人就无法提起。但是,在大多数关于机器人提升的研究中,通常认为“可行性”是先验存在的。本文提出了一种三步方法,用于类人机器人,以推理具有机器人未知的物理特性的重盒子的可行性。由于提升的可行性与盒子的物理属性直接相关,因此我们首先将描述这些属性的参数的未知值分散范围,并将所有有效的最佳准静态提升轨迹与所有索引组合相结合。其次,引入了基于物理相互作用的算法,以识别与盒子相对应的强大的抓地位置和物理参数。在此过程中,确保机器人的稳定性和安全性。在上述两个步骤的基础上,进行映射操作的第三步以最好地匹配估计参数与表中的索引。然后查询匹配的索引以确定是否存在有效的轨迹。如果是这样,提升运动是可行的。否则,机器人决定任务超出了其能力。我们的方法有效地评估了通过机器人和盒子之间的简单相互作用的提升任务的可行性,同时同时获得了所需的安全且稳定的轨迹。我们成功证明了使用NAO类人动物机器人提出的方法。

A robot cannot lift up an object if it is not feasible to do so. However, in most research on robot lifting, "feasibility" is usually presumed to exist a priori. This paper proposes a three-step method for a humanoid robot to reason about the feasibility of lifting a heavy box with physical properties that are unknown to the robot. Since feasibility of lifting is directly related to the physical properties of the box, we first discretize a range for the unknown values of parameters describing these properties and tabulate all valid optimal quasi-static lifting trajectories generated by simulations over all combinations of indices. Second, a physical-interaction-based algorithm is introduced to identify the robust gripping position and physical parameters corresponding to the box. During this process, the stability and safety of the robot are ensured. On the basis of the above two steps, a third step of mapping operation is carried out to best match the estimated parameters to the indices in the table. The matched indices are then queried to determine whether a valid trajectory exists. If so, the lifting motion is feasible; otherwise, the robot decides that the task is beyond its capability. Our method efficiently evaluates the feasibility of a lifting task through simple interactions between the robot and the box, while simultaneously obtaining the desired safe and stable trajectory. We successfully demonstrated the proposed method using a NAO humanoid robot.

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