Chance-Constrained Rollover-Free Manipulation Planning With Uncertain Payload Mass

被引:2
|
作者
Song, Jiazhi [1 ]
Petraki, Antoine [1 ]
Dehart, Brandon J. [2 ]
Sharf, Inna [1 ,3 ]
机构
[1] McGill Univ, Dept Mech Engn, Montreal, PQ H3A 0C3, Canada
[2] Univ Waterloo, Dept Elect & Comp Engn, Waterloo RoboHub, Waterloo, ON N2L 3G1, Canada
[3] FPInnovations, Pointe Claire, PQ H9R 3J9, Canada
关键词
Grasping; manipulators; motion planning; STABILITY; OPTIMIZATION; PREVENTION;
D O I
10.1109/TMECH.2023.3333793
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article presents a chance-constrained rollover-free manipulation planning method for robotic arms under payload mass uncertainty. The corresponding motion planning problem is stated as a chance-constrained nonlinear optimal control problem (NOCP) subject to kinematics and rollover stability constraints. The latter takes the form of a chance constraint that ensures a certain probability of the robot maintaining dynamic rollover stability in the presence of payload mass uncertainty. To achieve efficient solutions to the NOCP, a novel geometric bound for the stability region is derived. The novel bound is then utilized to modify the rollover-stability constraint. To showcase its benefit, comparisons between the proposed bound of probabilistic rollover-stability measure and the naive noise model are provided through statistical analysis. The formulation's practicality is demonstrated through experiments with a Kinova Jaco2 arm mounted on a free-to-rollover platform. Results demonstrate greater robustness of the robot's motion plan to mass uncertainty and computational efficiency of the trajectory generation.
引用
收藏
页码:2579 / 2589
页数:11
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