Abstract
In this paper, a new model is developed for a team of homogeneous and anonymous (no leader and follower) flocking robots to handle their online formation control, decision making, behavior selection, and motion planning while they simultaneously collect and shepherd a number of moving objects scattered in the workspace toward a predefined destination. Various complex flocking actions such as flock deformation, flock split and merge, flock expan-sion, and flock obstacle avoidance are incorporated in the model. Also, the paper proposes a new class of problems for flocking robots, called Simultaneous Object Collecting and Shepherding (SOCS) problem. The flock’s movement is governed using a fuzzy inference engine for determining the strategy of envi-ronment exploration (diversified search) or exploitation (move around a specific location), which provides an effective way to minimize the time spent on col-lecting objects while maximizing the gain obtained by object collection, in a way that the flock’s formation and integrity is maintained. Numerous simulations showed the effectiveness of the new model.
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Masehian, E., Royan, M. (2015). Cooperative Control of a Multi Robot Flocking System for Simultaneous Object Collection and Shepherding. In: Madani, K., Correia, A., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2012. Studies in Computational Intelligence, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-319-11271-8_7
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DOI: https://doi.org/10.1007/978-3-319-11271-8_7
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