Pedro Trueba
ABSTRACT
In this work, the canonical distributed embodied evolution algorithm used to solve a collective task in which a team of Micro Aerial Vehicles (MAVs) has to do surveillance in an indoor area. In order to efficiently survey the arena, the MAVs need to locate themselves and keep track of the recent covered areas and to share this information with other robots. This self-localization is performed using an IMU and a camera by means of artificial landmarks that can be sensed using the onboard camera and the position of other MAV in sight. The accuracy in the location of each MAV arises as a dynamic parameter and has been included as part of the problem to solve. Therefore, the collective control system is in charge of organizing the MAVs in order to increase the surveillance efficiency which is also subject to maintain a suitable accuracy for each of the MAVs.
- Haasdijk, E., Eiben, A.E., Karafotias, G. 2010. On-line evolution of robot controllers by an encapsulated evolution strategy, Proceedings IEEE CEC2010, 1--7Google Scholar
Cross Ref
- Bredeche, N., Montanier, J.M., Liu, W., Winfield, A. 2012. Environment-driven Distributed Evolutionary Adaptation in a Population of Autonomous Robotic Agents, Mathematical and Computational Modelling of Dynamical Systems 18, 1, 101--129Google ScholarCross Ref
- Trueba, P., Prieto, A., Bellas, F. 2013. Distributed embodied evolution for collective tasks: parametric analysis of a canonical algorithm, Proceedings GECCO2013, 37--3 Google ScholarDigital Library
Index Terms
- Embodied Evolution for Collective Indoor Surveillance and Location
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