A Real-Time Optimized Approach to Path Planning for Mobile Robot in Unknown Environment

您当前的位置：

首页 >

文章列表页 >

A Real-Time Optimized Approach to Path Planning for Mobile Robot in Unknown Environment

更新时间：2025-07-08

- A Real-Time Optimized Approach to Path Planning for Mobile Robot in Unknown Environment
- Acta Electronica Sinica Vol. 38, Issue 11, Pages: 2535-2539(2010)
- 作者机构：
  
  1. 北京化工大学信息科学与技术学院,北京,100029
  2. 同济大学嵌入式系统与服务计算教育部重点实验室,上海,201804
  3. 北京化工大学信息科学与技术学院北京,100029
  4. 同济大学嵌入式系统与服务计算教育部重点实验室上海,201804
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP24
- Published：2010
- 稿件说明：
移动端阅览
A Real-Time Optimized Approach to Path Planning for Mobile Robot in Unknown Environment[J]. Acta Electronica Sinica, 2010, 38(11): 2535-2539.
DOI：

A Real-Time Optimized Approach to Path Planning for Mobile Robot in Unknown Environment[J]. Acta Electronica Sinica, 2010, 38(11): 2535-2539. DOI：

摘要

针对未知环境下移动机器人的安全路径规划问题

提出一种基于改进神经网络和模拟退火算法相结合的方法.神经网络表示机器人的工作空间

通过BP反向算法学习外部环境结构特征和信息表示

进而优化障碍物神经网络的连接权值

利用模拟退火算法搜寻代价函数的负梯度方向

采用组合探测器来减小模拟退火算法搜索区域和应用后退策略及设置虚拟目标点的方法处理局部路径规划中出现的陷阱问题.仿真验证此方法有效性和正确性.

Abstract

For safe path planning of mobile robot in unknown environment

a method is proposed based on improved neural network and simulated annealing algorithm.Neural network is built to describe the working space of the mobile robot

which connection weights are optimized by the back propagation(BP) learning algorithm to study the structural features and information representation of the environment.Simulated annealing (SA) algorithm by using the combination of detectors to reduce the search area is adopted to get the best negative gradient direction of cost function.A strategy of back strategy and "virtual target" is introduced to deal with the problem of local minimum

which often occurs in local path planning.The result of the simulation experiment proves the effectiveness and feasibility of the proposed approach.

关键词

Keywords

references

Views

1860

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Low-Expansion A* Algorithm Based on CBS Framework for Complex Map

Improved Global Path Planning Algorithm Based on Ray Model

Dynamic Path Planning for Mobile Robot Based on Improved Ant Colony Optimization Algorithm

Mobile Robot Path Planning Based on Fuzzy Algorithms

The Framework Algorithm for Mobile Robot Simultaneous Localization and Mapping Based on PF/CUKF/EKF

Related Author

ZHANG Kai-xiang

MAO Jian-lin

XUAN Zhi-wei

FANG Dong-jun

JIANG Lin

HUANG Hui-bao

ZHOU He-wen

WU Hua

Related Institution

Faculty of Information Engineering and Automation, Kunming University of Science and Technology

Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology

Zhuhai A Micro Semiconductor Co. Ltd.

Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology

Institute of Robotics and Intelligent Systems, Wuhan University of Science and Technology

⁰