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Title of Journal: Neural Comput Applic

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Abbravation: Neural Computing and Applications

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Springer London

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DOI

10.1016/0041-1647(72)90129-3

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ISSN

1433-3058

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Vectorization path planning for autonomous mobile

Authors: QiLei Xu GongYou Tang
Publish Date: 2012/09/23
Volume: 23, Issue: 7-8, Pages: 2129-2135
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Abstract

This paper presents a novel realtime path planning algorithm called InsertBug for an autonomous mobile agent in completely unknown environment By using the algorithm all the planned paths are described and stored by vectors The algorithm combines range sensor data with safety radius to determine the blocking obstacles and calculate the shortest path by choosing the intermediate points When there is obstacle blocking the current path the intermediate points will be calculated and the planned path will be regenerated by inserting the intermediate points The local optimum avoidance strategy is also considered in this algorithm by specifying a fixed direction The agent will return to the optimal direction after running out of the local optimum Different simulation parameters are taken to show the advantages of this algorithm Moreover the performance of this algorithm has also been evaluated by comparing with another usual method via simulations The results show that the safety performance and time requirements of this algorithm are significant superior to the algorithm contrasted with

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