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SLAM-based maneuverability strategy for unmanned car-like vehicles

Published online by Cambridge University Press:  07 March 2013

Fernando A. Auat Cheein
Fernando A. Auat Cheein*
Affiliation:
Department of Electronics Engineering, Universidad Técnica Federico Santa María, Av. España 1680, Valparaíso, Chile
*
*Corresponding author. E-mail: fernando.auat@usm.cl
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Summary

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In this work, an optimal maneuverability strategy for car-like unmanned vehicles operating in restricted environments is presented. The maneuverability strategy is based on a path planning algorithm that uses the environment information to plan a safe, feasible and optimum path for the unmanned mobile robot. The environment information is obtained by means of a simultaneous localization and mapping (SLAM) algorithm. The SLAM algorithm uses the sensors' information to build a map of the surrounding environment. A Monte Carlo sampling technique is used to find an optimal and safe path within the environment based on the SLAM information. The objective of the planning is to safely reach a desired orientation in a bounded space. Theoretical demonstrations and real-time experimental results (in indoor and outdoor environments) are also presented in this work.

Keywords

Path planningSLAMUnmanned vehicles

Information

Type
Articles
Information
Robotica , Volume 31 , Issue 6 , September 2013, pp. 905 - 921
Copyright
Copyright © Cambridge University Press 2013 

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