Provably Safe Tolerance Estimation for Robot Arms via Sum-of-Squares Programming
Provably Safe Tolerance Estimation for Robot Arms via Sum-of-Squares Programming
复制标题
通过平方和编程对机器人手臂进行可证明安全的公差估计
DOI：
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复制
发表时间：
2021
影响因子：
3
通讯作者：
Changliu Liu
中科院分区：
文献类型：
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作者：
Weiye Zhao;Suqin He;Changliu Liu
公差估计问题在工程应用中普遍存在。例如，在现代机器人学中，有效地估计关节公差，即与参考机器人状态的最大允许偏差，以便仍然满足安全约束，仍然是具有挑战性的。本文提出了一种利用平方和规划估计关节公差的有效算法。从理论上证明了该算法给出了关节公差的下界。大量的数值研究表明，该方法具有计算效率高、近似最优的特点。
Tolerance estimation problems are prevailing in engineering applications. For example, in modern robotics, it remains challenging to efficiently estimate joint tolerance, i.e., the maximal allowable deviation from a reference robot state such that safety constraints are still satisfied. This letter presents an efficient algorithm to estimate the joint tolerance using sum-of-squares programming. It is theoretically proved that the algorithm provides a lower bound of the joint tolerance. Extensive numerical studies demonstrate that the proposed method is computationally efficient and near optimal.