运动规划
移动机器人
计算机科学
路径(计算)
遗传算法
并行计算
算法
实时计算
机器人
人工智能
计算机网络
机器学习
作者
Ching‐Chih Tsai,Hsu‐Chih Huang,Cheng-Kai Chan
出处
期刊:IEEE Transactions on Industrial Electronics
[Institute of Electrical and Electronics Engineers]
日期:2011-10-01
卷期号:58 (10): 4813-4821
被引量:259
标识
DOI:10.1109/tie.2011.2109332
摘要
This paper presents a parallel elite genetic algorithm (PEGA) and its application to global path planning for autonomous mobile robots navigating in structured environments. This PEGA, consisting of two parallel EGAs along with a migration operator, takes advantages of maintaining better population diversity, inhibiting premature convergence, and keeping parallelism in comparison with conventional GAs. This initial feasible path generated from the PEGA planner is then smoothed using the cubic B-spline technique, in order to construct a near-optimal collision-free continuous path. Both global path planner and smoother are implemented in one field-programmable gate array chip utilizing the system-on-a-programmable-chip technology and the pipelined hardware implementation scheme, thus significantly expediting computation speed. Simulations and experimental results are conducted to show the merit of the proposed PEGA path planner and smoother for global path planning of autonomous mobile robots.
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