Path planning of a snake-like robot based on serpenoid curve and genetic algorithms
Path planning of a snake-like robot based on serpenoid curve and genetic algorithms
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DOI：
10.1109/wcica.2004.1343634
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发表时间：
2004-06
期刊：
影响因子：
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通讯作者：
Jinguo Liu;Yuechao Wang;Bin;S. Ma
中科院分区：
文献类型：
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作者：
Jinguo Liu;Yuechao Wang;Bin;S. Ma
蛇形机器人的运动受地面条件、机构振动、电机电压变化等多种不确定因素的影响，路径无重复性。针对沈阳自动化学院(沈阳自动化学院，中国)蛇形机器人的路径规划问题，提出了一种基于蛇形曲线和遗传算法的路径规划方法。首先，对路径和曲率偏差的范围进行近似计算，并将其作为遗传算法的界。然后利用实时对偶遗传算法，该路径规划技术不仅可以确定最短路径和最小曲率偏差，而且可以限制运动误差的影响。仿真结果表明，第二层遗传算法得到的结果比第一层遗传算法的结果更有效，这对于SIA蛇形机器人的路径规划是有效的。
The path of the snake-like robot has no repetition because its motion is influenced by manifold indeterminate factors such as ground condition, mechanism's vibration and motor voltage's variety. A novel path planning technique based on serpenoid curve and genetic algorithms (GAs) has been proposed to control the snake-like robot in Shenyang Institute of Automation (SIA, China). First, the ranges of the path and the curvature deviation have been calculated approximately and set as the bounds of genetic algorithms. Then using real time dual genetic algorithms, this path planning technique not only can decide the shortest path and the minimum curvature deviation, but also can limit the motion error's influence. Simulation results show that the results of the second layer of GAs are more available than that of the first layer of GAs and this novel technique is effective for the path planning of the SIA snake-like robot.