Abstract
This paper addresses the problem of automatic parallel parking by a back-wheel drive vehicle, using a biomimetic model based on direct coupling between vehicle perceptions and actions. This problem is solved by means of a bio-inspired approach in which the vehicle controller does not need to know the car kinematics and dynamics, neither does it call for a priori knowledge of the environment map. The key point in the proposed approach is the definition of performance indices that for automatic parking happen to be functions of the strategic orientations to be injected, in real time, to the car-like robot controller. This solution leads to a dynamic multi-objective optimization problem, which is extremely hard to be dealt with analytically. A genetic algorithm is therefore applied, thanks to which we obtain a very simple and efficient solution. The paper ends with the results of computer simulations.
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© 2005 Springer-Verlag Berlin Heidelberg
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de Lope, J., Maravall, D. (2005). Multi-objective Dynamic Optimization for Automatic Parallel Parking. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2005. EUROCAST 2005. Lecture Notes in Computer Science, vol 3643. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556985_66
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DOI: https://doi.org/10.1007/11556985_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29002-5
Online ISBN: 978-3-540-31829-3
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