基于改进人工势场的移动服务机器人路径规划算法

Min Song, Junyou Yang, Yina Wang, Chunwei Yu, Donghui Zhao
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引用次数: 4

摘要

路径规划是机器人研究的重要领域之一。然而,每种路径规划算法都有其不足之处。经典的人工势场(APF)算法可以为移动机器人规划路径。但由于算法的运行机制,存在局部最小值和振动问题。改进算法的思想是通过设置子目标,在机器人陷入局部最小或振动区域时进行转弯,并通过设置虚拟减振圆来避免大部分振动。此外,改进算法利用全局模型信息简化了机器人在路径中所面临的环境。仿真结果表明,改进算法为机器人规划了一条更平滑、振动更小的路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Path Planning Algorithm Based on an Improved Artificial Potential Field for Mobile Service Robots
The path planning is one of the significant domains in robotics. However, every algorithm for path planning has disadvantages. The classical Artificial Potential Field(APF) algorithm can plan a path for mobile robot. However, there are local minimum and vibration problems due to the algorithm's operation mechanism. The idea of improved algorithm is to make a turn when robot sinks into the local minimum or vibration region by setting a sub-goal, and avoid most vibration by setting a virtual anti-vibrate circle. Furthermore, the improved algorithm takes advantage of global model information to simplify the environment the robot is faced with in the path. The simulation results show that the improved algorithm plan a smoother and less vibrating path for the robot.
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