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Research on Path Planning for Mobile Robot Based on the Genetic Algorithm

Author: JiangMingYang
Tutor: HuYuLan
School: Shenyang University of Technology
Course: Detection Technology and Automation
Keywords: Mobile robot Path planning Genetic Algorithms
CLC: TP242
Type: Master's thesis
Year: 2008
Downloads: 413
Quote: 1
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Abstract


Intelligent mobile robot without human intervention , can complete autonomy vehicles driving task . Path planning is a core issue in the field of robotics research , and its mission is in the environment with obstacles and seek the one known from a known starting point to the end of the collision-free path with the lowest price . The genetic algorithm is a randomized , iterative and evolutionary process based on natural selection and population genetics , is a very effective algorithm path planning in the field of research . The paper first discusses the theory of mobile robot path planning method , the comparative advantages and disadvantages of various path planning method , select the genetic algorithm to solve the path planning problem of mobile robot . And then , through in-depth study of the genetic algorithm for robot path planning in static and dynamic environment , the paper proposes a solution based on genetic algorithms . The design of genetic operators a smooth , insert and delete operators to supplement the lack of basic operators adaptive mutation rate and crossover rate adjustment method of genetic algorithm optimization . By adding a new operator and adaptive adjustment method can make the algorithm more perfect solution fall into local minimum in the evolutionary process and can not reach the target point . Finally , in the the three complexity of different static environment , simulation experiment and simulation results analysis discussed different fitness parameters on the results of path planning , dynamic path planning simulation . With other methods comparison can be found under the same environment , the path planning method based on genetic algorithms in search time than the Di jkstra algorithm to save at least 5% of the time ; in the path length and smoothness , path planning method based on genetic algorithms better than artificial potential field algorithm . Through this study and the experimental results prove that the genetic algorithm can be a good solution to the path planning problem of mobile robot in dynamic and static environments .

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Robotics > Robot
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