论文标题
用共同抓握操纵
Manipulation with Shared Grasping
论文作者
论文摘要
共享的掌握是由操纵对象与机器人手和环境之间的接触形成的掌握。通过将手触点交换以获取环境联系，共享的掌握需要更少的与手接触，即使无法完全掌握，也可以操纵操作。先前的研究使用了共享的掌握，进行了非划出的操作，例如旋转和翻滚。本文通过方法更普遍地对待问题，以选择最佳的共享掌握和机器人动作来进行所需的对象运动。中心问题是评估可行的接触模式：对于每个接触，该联系人是否保持活跃以及是否会发生滑动。鲁棒性很重要。当触点模式失败时，例如，当触点丢失或发生无意的滑移时，操作将失败，在某些情况下可能会造成损害。在这项工作中，我们列举所有可行的接触模式，计算相应的控件，然后选择最强大的候选者。我们还可以优化触点几何形状以符合鲁棒性。本文对具有库仑摩擦的平面刚体进行了准静态分析，以得出算法和对照。最后，我们证明了共享抓地力的鲁棒性以及在代表性实验和示例中使用我们的方法。该视频可以在https://youtu.be/tynhjvryznk上找到
A shared grasp is a grasp formed by contacts between the manipulated object and both the robot hand and the environment. By trading off hand contacts for environmental contacts, a shared grasp requires fewer contacts with the hand, and enables manipulation even when a full grasp is not possible. Previous research has used shared grasps for non-prehensile manipulation such as pivoting and tumbling. This paper treats the problem more generally, with methods to select the best shared grasp and robot actions for a desired object motion. The central issue is to evaluate the feasible contact modes: for each contact, whether that contact will remain active, and whether slip will occur. Robustness is important. When a contact mode fails, e.g., when a contact is lost, or when unintentional slip occurs, the operation will fail, and in some cases damage may occur. In this work, we enumerate all feasible contact modes, calculate corresponding controls, and select the most robust candidate. We can also optimize the contact geometry for robustness. This paper employs quasi-static analysis of planar rigid bodies with Coulomb friction to derive the algorithms and controls. Finally, we demonstrate the robustness of shared grasping and the use of our methods in representative experiments and examples. The video can be found at https://youtu.be/tyNhJvRYZNk
