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Path Planning Method for Robot Based on Differential Evolution Algorithm

Author: ZhangXiaoLi
Tutor: YuBo
School: Dalian University of Technology
Course: Computational Mathematics
Keywords: Robot Path planning Differential evolution algorithm
CLC: O221
Type: Master's thesis
Year: 2006
Downloads: 331
Quote: 7
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Abstract


With the extensive application of artificial intelligence , robotics as one of the branches has been rapid development. Robotics is a modern information technology and advanced manufacturing technologies and a typical representative of the main technical means , and become the world competing for the development of the scientific frontiers . Path planning techniques in the field of robotics research is an important branch . It is a very complex issue with obstacles in the environment, according to an evaluation criteria ( such as the shortest path length , the shortest travel time , minimum energy consumption, etc. ) , plan a starting position to the target point from the optimal position ( or suboptimal ) collision -free path . Its main contents expression involving environmental , planning methods , path search and artificial intelligence and other disciplines . Adopt good robot path planning techniques can save a lot of Android operating time, reduce robot wear and tear , but can also save manpower resources, reduce capital investment for robot applications in a variety of industries to lay a good foundation. About path planning algorithm has long been concern and attention by people , people from many aspects of exploration and research , although some success , but there are still many issues to be studied in depth . This thesis analyzes the current advantages and disadvantages of various path planning method is proposed based on a novel differential evolution algorithm for robot path planning method . Path planning problem for the characteristics of the various aspects of the algorithm a detailed analysis , including maps built environment , individual representation and fitness function design, differential evolution operators were the design, analysis and selection algorithm parameters . Finally simulation program written using VC 6.0 , in a static environment for simulation. Simulation results show that the algorithm can successfully in a variety of environments of varying complexity approximate optimal planning out a path to prove the effectiveness of the algorithm .

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CLC: > Mathematical sciences and chemical > Mathematics > Operations Research > Planning Theory ( mathematical programming)
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