Optimal redundancy resolution for cooperative industrial robots

B. Cao, G. Dodds, G. Irwin
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Abstract

Planning for effective manipulation of single, redundant or multiple robot systems requires the consideration of the DOF, dexterity, tasks and constraints. A new approach to redundancy resolution for multiple cooperative robots is proposed. A relative Jacobian, thus relative dexterity, is clearly defined and derived for multiple robots. Sequential quadratic programming (SQP) is used to optimize the relative dexterity of the robots whilst satisfying task requirements and limits on joint angles. With this approach it is not necessary to balance the weightings between the performance index and those constraint terms in the cost function. Further the resulting joint configurations are globally optimal with respect to the specified cost. An illustrative example is included to demonstrate the usefulness of this approach. From this example, the relative dexterity of the arms has been found to be more useful than individual arm dexterities in planning the cooperative task.
协作型工业机器人的最优冗余分辨率
规划单个、冗余或多个机器人系统的有效操作需要考虑自由度、灵巧性、任务和约束。提出了一种新的多协作机器人冗余度求解方法。明确定义并推导了多个机器人的相对雅可比矩阵,即相对灵巧度。在满足任务要求和关节角度限制的前提下,采用序列二次规划方法优化机器人的相对灵巧度。使用这种方法,不需要平衡性能指标和成本函数中约束项之间的权重。此外,所得到的关节构型在给定成本下是全局最优的。其中包括一个说明性示例来演示这种方法的有用性。从这个例子中,我们发现在规划合作任务时,手臂的相对灵巧度比单个手臂的灵巧度更有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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