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Assessment of an ant-inspired algorithm for path planning

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dc.contributor.author Viswanathan, Sangeetha
dc.date.accessioned 2024-10-25T06:49:49Z
dc.date.available 2024-10-25T06:49:49Z
dc.date.issued 2022
dc.identifier.uri https://www.sciencedirect.com/science/article/pii/B9780128210536000163
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16190
dc.description.abstract The demand for path planners for a variety of applications has significantly increased over the past decade. The correct choice of a distance metric will be of utmost importance for an efficient path planner. The underlying connectivity of the roadmaps produced by the planner are determined by the metrics. A study was conducted in this chapter for the proper choice of planner metrics. Five metrics from the literature were chosen and implemented in a gain-based ant colony optimization (GACO) algorithm. Results are analyzed against parameters, such as time taken, length of the path, and turn characteristics. Finally, the GACO with the chosen metric was implemented using different satellite images from the International Society for Photogrammetry and Remote Sensing and compared against existing algorithms with respect to performance. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.subject Computer Science en_US
dc.subject Ant colony optimization en_US
dc.subject Ant system en_US
dc.subject Remote Sensing en_US
dc.subject Sigmoid function en_US
dc.subject Turn characteristics en_US
dc.title Assessment of an ant-inspired algorithm for path planning en_US
dc.type Article en_US


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