论文标题
双手任务的强大相对手部放置
Robust Relative Hand Placement For Bi-Manual Tasks
论文作者
论文摘要
在许多双重机器人任务中，例如钉上孔组件，任务执行的成功取决于在插入前配置中实现PEG和孔之间所需的相对姿势的错误。关节空间中的随机致动误差通常会阻止两个臂达到所需的任务空间，这又导致两只手之间的相对姿势随机误差。随机误差因试验而异，因此取决于钉和孔之间的公差，组装任务的结果可能是随机的（有时任务执行成功，有时会失败）。通常，由于相对姿势的自由度为6美元，因此两个臂的关节空间解决方案数量无限，与相同的任务空间相对姿势相对应。但是，在有驱动误差的情况下，关节空间解决方案并非全部相同，因为它们映射了关节空间误差以不同于任务空间的设置。因此，本文的目的是开发一种有条理的方法来计算关节空间解决方案，以使最大任务空间误差低于A（指定）阈值，概率很高。这种解决方案称为双手机器人的稳健逆运动解。我们提出的方法还允许机器人自我评估是否可以可靠地执行给定的双手任务。我们在双臂Baxter机器人上使用平方钉在孔组装方案上，以显示我们方法实用性的数值模拟。
In many bi-manual robotic tasks, like peg-in-a-hole assembly, the success of the task execution depends on the error in achieving the desired relative pose between the peg and the hole in a pre-insertion configuration. Random actuation errors in the joint space usually prevent the two arms from reaching their desired task space poses, which in turn results in a random error in relative pose between the two hands. This random error varies from trial to trial, and thus depending on the tolerance between the peg and the hole, the outcome of the assembly task may be random (sometimes the task execution succeeds and sometimes it fails). In general, since the relative pose has $6$ degrees-of-freedom, there are infinite numbers of joint space solutions for the two arms that correspond to the same task space relative pose. However, in the presence of actuation errors, the joint space solutions are not all identical since they map the joint space error sets differently to the task space. Thus, the goal of this paper is to develop a methodical approach to compute a joint space solution such that the maximum task space error is below a (specified) threshold with high probability. Such a solution is called a robust inverse kinematics solution for the bi-manual robot. Our proposed method also allows the robot to self-evaluate whether it can perform a given bi-manual task reliably. We use a square peg-in-a-hole assembly scenario on the dual-arm Baxter robot for numerical simulations that shows the utility of our approach.
