Predictive joint trajectory scaling for manipulators with kinodynamic constraints

被引:19
作者
Faroni, Marco [1 ]
Beschi, Manuel [1 ]
Lo Bianco, Corrado Guarino [2 ]
Visioli, Antonio [3 ]
机构
[1] CNR, Ist Sistemi & Tecnol Ind Intelligenti Manifatturi, Milan, Italy
[2] Univ Parma, Dipartimento Ingn & Architettura, Parma, Italy
[3] Univ Brescia, Dipartimento Ingn Meccan & Ind, Brescia, Italy
基金
欧盟地平线“2020”;
关键词
Motion planning; Robot manipulators; Trajectory scaling; Joint constraints; Predictive control; INVERSE KINEMATICS; IMPLEMENTATION; CONTROLLER;
D O I
10.1016/j.conengprac.2019.104264
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Trajectory scaling techniques adapt online the robot timing law to preserve the desired geometric path when the desired motion does not respect the robot limits. State-of-the-art non-predictive methods typically provide far-from-optimal solutions, while high computational burdens are the main bottleneck for the implementation of receding horizon strategies. This paper proposes a predictive approach to trajectory scaling subject to joint velocity, acceleration, and torque limitations. Computational complexity is dramatically reduced by means of the parametrization of inputs and outputs and the iterative linearization of the optimal control problem around the previous output prediction. This allows the online implementation of the method for sampling periods in the order of one millisecond. Numerical and experimental results on a six-degree-of-freedom robot show the effectiveness of the method.
引用
收藏
页数:9
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