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Thorough Review Analysis of Safe Control of Autonomous Vehicles: Path Planning and Navigation Techniques

Sara Abdallaoui, El-Hassane Aglzim, Ahmed Chaibet and Ali Kribèche
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Sara Abdallaoui: DRIVE Laboratory EA1859, University of Bourgogne Franche Comté, F58000 Nevers, France
El-Hassane Aglzim: DRIVE Laboratory EA1859, University of Bourgogne Franche Comté, F58000 Nevers, France
Ahmed Chaibet: DRIVE Laboratory EA1859, University of Bourgogne Franche Comté, F58000 Nevers, France
Ali Kribèche: DRIVE Laboratory EA1859, University of Bourgogne Franche Comté, F58000 Nevers, France

Energies, 2022, vol. 15, issue 4, 1-19

Abstract: Mobile robot path planning has passed through multiple phases of development and took up several challenges. Up to now and with the new technology in hands, it becomes less complicated to conduct path planning for mobile robots and avoid both static and dynamic obstacles, so that collision-free navigation is ensured. Thorough state of the art review analysis with critical scrutiny of both safe and optimal paths for autonomous vehicles is addressed in this study. Emphasis is given to several developed techniques based using sampling algorithms, node-based optimal algorithms, mathematic model-based algorithms, bio-inspired algorithms, which includes neural network algorithms, and then multi-fusion-based algorithms, which combine different methods to overcome the drawbacks of each. All of these approaches consider different conditions and they are used for multiple domains.

Keywords: mobile robots; path planning; obstacle avoidance; optimal control; navigation systems (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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