Kinematic Control of Redundant Manipulators: Generalizing the Task-Priority Framework to Inequality Task
Kinematic Control of Redundant Manipulators: Generalizing the Task-Priority Framework to Inequality Task
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DOI：
10.1109/tro.2011.2142450
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发表时间：
2011-08-01
影响因子：
7.8
通讯作者：
Wieber, Pierre-Brice
中科院分区：
文献类型：
--
作者：
Kanoun, Oussama;Lamiraux, Florent;Wieber, Pierre-Brice
像人形机器人这样的冗余机械系统被设计成一次完成多项任务。在速度分辨逆运动学中，任务是机器人配置的函数的期望值，该期望值可以用常微分方程（ODE）来调节。当面对同时的任务时，相应的方程可以被分组在一个系统中，或者更好地，按优先级排序，并在更高优先级任务的解决方案集中求解每个方程。这个优雅的分层任务调节框架已被实现为一系列最小二乘问题。它的局限性在于处理不等式约束，通常通过势场将不等式约束转化为更严格的等式约束。在本文中，我们提出了一个新的优先任务监管框架的基础上的序列的二次规划（QP），消除了限制。在该算法的基础上，研究了由QP序列产生的最优集合。该算法的实现和仿真说明的仿人机器人HRP-2。
Redundant mechanical systems like humanoid robots are designed to fulfill multiple tasks at a time. A task, in velocity-resolved inverse kinematics, is a desired value for a function of the robot configuration that can be regulated with an ordinary differential equation (ODE). When facing simultaneous tasks, the corresponding equations can be grouped in a single system or, better, sorted in priority and solved each in the solutions set of higher priority tasks. This elegant framework for hierarchical task regulation has been implemented as a sequence of least-squares problems. Its limitation lies in the handling of inequality constraints, which are usually transformed into more restrictive equality constraints through potential fields. In this paper, we propose a new prioritized task-regulation framework based on a sequence of quadratic programs (QP) that removes the limitation. At the basis of the proposed algorithm, there is a study of the optimal sets resulting from the sequence of QPs. The algorithm is implemented and illustrated in simulation on the humanoid robot HRP-2.