Fast Robot Motion Planning with Collision Avoidance and Temporal Optimization

被引：0
|
作者：
Lin, Hsien-Chung [1 ,2 ]
Liu, Changliu [1 ,3 ]
Tomizuka, Masayoshi [1 ]
机构：
[1] Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA
[2] FANUC Adv Res Lab, Union City, CA 94587 USA
[3] Stanford Univ, Stanford, CA 94305 USA
来源：
2018 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV) | 2018年
基金：
美国国家科学基金会;
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Considering the growing demand of real-time motion planning in robot applications, this paper proposes a fast robot motion planner (FRMP) to plan collision-free and time-optimal trajectories, which applies the convex feasible set algorithm (CFS) to solve both the trajectory planning problem and the temporal optimization problem. The performance of CFS in trajectory planning is compared to the sequential quadratic programming (SQP) in simulation, which shows a significant decrease in iteration numbers and computation time to converge a solution. The effectiveness of temporal optimization is shown on the operational time reduction in the experiment on FANUC LR Mate 200iD/7L.
引用
收藏
页码：29 / 35
页数：7
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