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Safe Navigation Strategies within Cluttered Environment

Abstract : This thesis pertains to optimization-based navigation and control in multi-obstacle environments. The design problem is commonly stated in the literature in terms of a constrained optimization problem over a non-convex domain. Thus, building on the combination of Model Predictive Control and set-theoretic concepts, we develop a couple of constructive methods based on the geometrical interpretation. In its first part, the thesis focuses based on a thorough analysis of the recent results in the field on the multi-obstacle environment's representation. Hence, we opted to exploit a particular class of convex sets endowed with the symmetry property to model the environment, reduce complexity, and enhance performance. Furthermore, we solve an open problem in navigation within cluttered environments: the feasible space partitioning in accordance with the distribution of obstacles. This methodology's core is the construction of a convex lifting which boils down to convex optimization. We cover both the mathematical foundations and the computational details of the implementation. Finally, we illustrate the concepts with geometrical examples, and we complement the study by further providing global feasibility guarantees and enhancing the effective control by operating at the strategical level.
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Contributor : Abes Star :  Contact Connect in order to contact the contributor
Submitted on : Monday, October 4, 2021 - 12:06:11 PM
Last modification on : Monday, October 11, 2021 - 12:35:20 PM


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  • HAL Id : tel-03363948, version 1


Daniel Ioan. Safe Navigation Strategies within Cluttered Environment. Automatic. Université Paris-Saclay, 2021. English. ⟨NNT : 2021UPASG047⟩. ⟨tel-03363948⟩



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