运动规划
计算机科学
碰撞检测
随机树
移动机器人
花键(机械)
完整的
机器人
路径(计算)
运动学
算法
数学优化
快速行进算法
平滑的
碰撞
人工智能
数学
计算机视觉
工程类
物理
程序设计语言
经典力学
结构工程
计算机安全
作者
S. A. Eshtehardian,S. Khodaygan
标识
DOI:10.1007/s12652-021-03625-8
摘要
Rapidly exploring random trees (RRT) are sampling-based approaches being widely applied for path planning of mobile robots. Since the output of these algorithms usually is a stream of discrete lines involving discontinuity at the linking points, kinematic constraints restrict the robot's movements. Consequently, robots may not pass discrete points in the path correctly. Hence, the using CAGD (Computer-Aided Geometry Design) curves can run simultaneously alongside those algorithms or may run after that to make a smooth path and that's the way in which non-holonomic constraints can be considered perfect and robots can be droved autonomously across them about the collision detection method which executed by the main sampling-based algorithm like RRT*. In this paper, an approach based on the combination of RRT* and B-spline is proposed for smoothing the path which is generated by RRT*-based algorithms, which are one of the most famous groups of algorithms in artificial intelligence. Some new functions are added to the outcome of the RRT* algorithm. To avoid collision in the generated path, some corrections are also provided. Finally, for illustrating the efficiency of the proposed method, the algorithm is implemented in the simulation environment of Webots® and for verification, the obtained results are compared and discussed.
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