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Graph Based Path Planning

Graph Based Path Planning

Copyright: © 2013 |Pages: 28
ISBN13: 9781466620742|ISBN10: 1466620749|EISBN13: 9781466620759
DOI: 10.4018/978-1-4666-2074-2.ch002
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MLA

Ritu Tiwari, et al. "Graph Based Path Planning." Intelligent Planning for Mobile Robotics: Algorithmic Approaches, IGI Global, 2013, pp.26-53. https://doi.org/10.4018/978-1-4666-2074-2.ch002

APA

R. Tiwari, A. Shukla, & R. Kala (2013). Graph Based Path Planning. IGI Global. https://doi.org/10.4018/978-1-4666-2074-2.ch002

Chicago

Ritu Tiwari, Anupam Shukla, and Rahul Kala. "Graph Based Path Planning." In Intelligent Planning for Mobile Robotics: Algorithmic Approaches. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2074-2.ch002

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Abstract

Graphs are keenly studied by people of numerous domains as most of the applications we encounter in our daily lives can be easily given a graph-based representation. All the problems may then be easily studied as grap-based problems. In this chapter, the authors study the problem of robot motion planning as a graph search problem. The key steps involve the representation of the problem as a graph and solving the problem as a standard graph search problem. A number of graph search algorithms exist, each having its own advantages and disadvantages. In this chapter, the authors explain the concept, working methodology, and issues associated with some of these algorithms. The key algorithms under discussion include Breadth First Search, Depth First Search, A* Algorithm, Multi Neuron Heuristic Search, Dijkstra’s Algorithm, D* Algorithm, etc. Experimental results of some of these algorithms are also discussed. The chapter further presents the advantages and disadvantages of graph-based motion planning.

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