Investigating an A-star algorithm-based fitness function for mobile robot evolution

Conference paper


Shanker Prabhu, Kyberd, P. and Jodie Wetherall 2018. Investigating an A-star algorithm-based fitness function for mobile robot evolution. 2018 22nd International Conference on System Theory, Control and Computing (ICSTCC). Romania 10 - 12 Oct 2018 IEEE Xplore. https://doi.org/10.1109/icstcc.2018.8540734
AuthorsShanker Prabhu, Kyberd, P. and Jodie Wetherall
TypeConference paper
Abstract

<p>One of the factors that affect the success of Evolutionary Robotics (ER) is the way fitness functions are designed to operate. While needs-based custom fitness functions have been developed, most of the time they have been defined in simpler mathematical functions to reduce the computation time. In this paper, we hypothesize that an incremental fitness function based on established techniques in specific task domains in robotics will aid the evolution process. An A-star algorithm-based fitness function for path planning is designed and implemented for evolving the body plans and controllers of robots for navigation and obstacle avoidance tasks. It has been shown that using this concept, fitter robots have evolved in most cases when compared to simple distance-only based fitness functions. However, due to variable performance of the evolver with the A-star fitness function, the results are inconclusive. We also identify problems associated with the fitness function and make recommendations for designing future fitness functions based on observations of the experiments.</p>

KeywordsEvolutionary robotics; fitness functions; A-star algorithm; task domains
Year2018
Conference 2018 22nd International Conference on System Theory, Control and Computing (ICSTCC)
Journal2018 22nd International Conference on System Theory, Control and Computing, ICSTCC 2018 - Proceedings
PublisherIEEE Xplore
ISSN2372-1618
Digital Object Identifier (DOI)https://doi.org/10.1109/icstcc.2018.8540734
Web address (URL)https://researchportal.port.ac.uk/en/publications/c1eefcfd-a689-4111-b7b1-ca500589dc68
Journal citation(Article: 8540734), pp. 771 - 776
ISBN9781538644447
9781538644454
Web address (URL) of conference proceedingshttps://ieeexplore.ieee.org/xpl/conhome/8514498/proceeding
Output statusPublished
Publication dates22 Nov 2018
Publication process dates
Deposited01 Jun 2023
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