Abstract
The navigation of groups of robots, especially multirobot systems (MRS) or even swarm robots, has been one of the fields that has benefited from biological inspiration (Bonabeau et al., Proceedings of the 2000 IEEE International Conference on Robotics, 1999). As with many other things in robotics, the advances were first introduced and evaluated in the context of computer agents. One of the first applications of those methods started with optimization tools with the well-known particle swarm optimization (PSO) previously mentioned. In this chapter, we try to go a step forward by adapting the version of the FODPSO to MRS, denoting it robotic DPSO (RDPSO). Any other PSO variant could be adapted to MRS exploration. However, the FODPSO was chosen because it is an evolutionary algorithm that extends the PSO using natural selection to enhance the ability to escape from suboptimal solutions and employs fractional calculus to improve the convergence of particles.
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Notes
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Process where certain individuals are excluded from particular sorts of social interactions.
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Couceiro, M., Ghamisi, P. (2016). Case Study III: Swarm Robotics. In: Fractional Order Darwinian Particle Swarm Optimization. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-19635-0_5
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