This paper derives a closed-form method for computing hybrid force-velocity control. The key idea is to maximize the kinematic conditioning of the mechanical system, which includes a robot, free objects, a rigid environment and contact constraints. The method is complete, in that it always produces an optimal/near optimal solution when a solution exists. It is efficient, since it is in closed form, avoiding the iterative search of previous work. We test the method on 78,000 randomly generated test cases. The method outperforms our previous search-based technique by being from 7 to 40 times faster, while consistently producing better solutions in the sense of robustness to kinematic singularity. We also test the method in several representative manipulation experiments.
翻译:本文提出了一种计算混合力速度控制的封闭式方法。 关键的想法是使机械系统, 包括机器人、 自由天体、 僵硬环境和接触限制的动力调节最大化。 这种方法是完整的, 因为它总是在解决方案存在时产生最佳/ 近于最佳的解决方案。 它非常有效, 因为它是封闭式的, 避免了对先前工作的迭接搜索。 我们测试了78 000个随机生成的测试案例。 这种方法比我们先前的搜索技术快7至40倍, 同时从强到运动奇特的意义上不断产生更好的解决方案。 我们还在几项有代表性的操作实验中测试了该方法。