Abstract
This paper presents an application of the emerging Cohort Intelligence (CI) algorithm in the domain of swarm robotics. The application could be relevant to search and rescue in alien territory as well as establishment. The robots are considered as candidates in the CI algorithm. An exponential probability approach is proposed by which every candidate/robot decide to follow one another. In this approach, the probability of following the worse candidate decreases and the probability stake of the better candidate increases. This makes the robots more biased to follow better candidates. This helps to reduce the randomness in the system. The approach was applied and validated by solving path planning and obstacle avoidance for application of a swarm of robots in a static and unknown environment. The cases such as No Obstacle Case (NOC), Rectangular Obstacle Case (ROC), Multiple Rectangular Obstacles Case (MROC) and Cluttered Polygonal Obstacles Case (CPOC) were solved. The results obtained were better in terms of computational time and function evaluations as compared to the linear probability distributions approach. The limitations of the approach solving the obstacle avoidance for swarm of robots are also discussed.
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References
Abed-alguni BH, Chalup SK, Henskens FA (2015) A multi-agent cooperative reinforcement learning model using a hierarchy of consultants, tutors and workers. Vietnam J Comput Sci 2:213. https://doi.org/10.1007/s40595-015-0045-x
Burion S (2004) Human detection for robotic urban search and rescue, Thesis submitted to Ecole Polytechnic
Dhavle SV, Kulkarni AJ, Shastri A, Kale IR (2017) Design and economic optimization of shell-and-tube heat exchanger using cohort intelligence algorithm. Neural Comput Appl (In Press)
Gaikwad S, Joshi R, Kulkarni AJ (2015) Cohort intelligence and genetic algorithm along with modified analytical hierarchy process to recommend an ice cream to a diabetic patient. In: Satpathy, Bhateja, Joshi (eds) Advances in intelligent and soft computing, vol 468, pp 279–288. Springer
Gaikwad S, Joshi R, Kulkarni AJ (2016) Cohort intelligence and genetic algorithm along with AHP to recommend an ice cream to a diabetic patient. Lecture Notes in Computer Science. Springer (In Press)
Grayson S (2014) Search & rescue using multi-robot systems, research report: trinity college Dublin. http://www.maths.tcd.ie/~graysons/documents/COMP47130_SurveyPaper.pdf
Krishnasamy G, Kulkarni AJ, Paramesaran R (2014) A hybrid approach for data clustering based on modified cohort intelligence and K-means. Expert Syst Appl 41(13):6009–6016
Kulkarni AJ, Baki MF, Chaouch BA (2016) Application of the cohort-intelligence optimization method to three selected combinatorial optimization problems. Europe J Op Res 250(2):427–447
Kulkarni AJ, Durugkar IP, Kumar M (2013) Cohort intelligence: a self supervised learning behavior. In: Proceedings of IEEE international conference on systems, man and cybernetics, pp 1396–1400. Manchester, UK, 13–16 Oct 2013
Kulkarni AJ, Krishnasamy G, Abraham A (2017) Cohort intelligence: a socio-inspired optimization method. In: Intelligent systems reference library, vol 114. Springer. https://doi.org/10.1007/978-3-319-44254-9, ISBN: 978-3-319-44254-9
Kulkarni AJ, Shabir H (2016) Solving 0–1 knapsack problem using cohort intelligence algorithm. Int J Mach Learn Cybernet 7(3):427–441
Kulkarni O, Kulkarni N, Kulkarni AJ, Kakandikar G (2016) Constrained cohort intelligence using static and dynamic penalty function approach for mechanical components design. Int J Parallel Emer Distrib Syst (In Press). https://doi.org/10.1080/17445760.2016.1242728
Shastri AS, Jadhav PS, Kulkarni AJ, Abraham A (2016) Solution to constrained test problems using cohort intelligence algorithm. In: Advances in intelligent and soft computing, vol 424, pp 427–435. Springer
Trigui S, Koubaa A, Cheikhrouhou O, Youssef H, Bennaceur H, Sriti M-F, Javed Y (2014) A distributed market-based algorithm for the multi-robot assignment problem. Proc Comput Sci 32:1108–1114
Yan Z, Jouandeau N, Cherif AA (2013) A survey and analysis of multi-robot coordination. Int J Adv Rob Syst 10:1–18
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Roychowdhury, P., Mehra, S., Devarakonda, R., Shrivastava, P., Basu, S., Kulkarni, A.J. (2019). A Self-organizing Multi-agent Cooperative Robotic System: An Application of Cohort Intelligence Algorithm. In: Kulkarni, A.J., Singh, P.K., Satapathy, S.C., Husseinzadeh Kashan, A., Tai, K. (eds) Socio-cultural Inspired Metaheuristics. Studies in Computational Intelligence, vol 828. Springer, Singapore. https://doi.org/10.1007/978-981-13-6569-0_2
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DOI: https://doi.org/10.1007/978-981-13-6569-0_2
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