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Jeon, Jeong hwan
Robotics and Mobility Lab.
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dc.citation.endPage 39727 -
dc.citation.startPage 39717 -
dc.citation.title IEEE ACCESS -
dc.citation.volume 12 -
dc.contributor.author Vo, Cong Phat -
dc.contributor.author Jung, Philjoon -
dc.contributor.author Kim, Tae-Hyun -
dc.contributor.author Jeon, Jeong hwan -
dc.date.accessioned 2024-06-13T15:35:12Z -
dc.date.available 2024-06-13T15:35:12Z -
dc.date.created 2024-06-13 -
dc.date.issued 2024-03 -
dc.description.abstract This paper presents an efficient motion planning framework for a perturbed linear system using a minimax objective function while ensuring the safety of the system. Specifically, the proposed approach is naturally deployed to handle model uncertainties by a recursive least squares-based set-membership mechanism. Next, a minimax-based objective optimization problem is formed to handle the goal flexibility. The robust model predictive control algorithm is then designed to solve this robust optimization objective. Furthermore, a refined strategy is able to approximate robust objectives by synergizing interval prediction and tree-based planning to achieve the best surrogate performance. It is extended to incorporate a hierarchical control architecture in a specific context. This extension serves to enhance path efficiency and, in turn, alleviates the constraints associated with modeling assumptions. The primary difficulty involves integrating and adjusting theoretical assurances at each level, a task accomplished through a comprehensive examination of suboptimality from end to end. The proposed framework is versatile across a variety of models, incorporating a solid, data-informed approach for selecting models. This integration permits a more flexible approach to modeling assumptions. Moreover, we consistently maintain the practicability of our method throughout its application, a fact that is evidenced by its successful deployment in complex simulated settings. -
dc.identifier.bibliographicCitation IEEE ACCESS, v.12, pp.39717 - 39727 -
dc.identifier.doi 10.1109/ACCESS.2024.3376253 -
dc.identifier.issn 2169-3536 -
dc.identifier.scopusid 2-s2.0-85188004752 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/82984 -
dc.identifier.wosid 001189838500001 -
dc.language 영어 -
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC -
dc.title Efficient Motion Planning With Minimax Objectives: Synergizing Interval Prediction and Tree-Based Planning -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.relation.journalWebOfScienceCategory Computer Science, Information Systems;Engineering, Electrical & Electronic;Telecommunications -
dc.relation.journalResearchArea Computer Science;Engineering;Telecommunications -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor model predictive control -
dc.subject.keywordAuthor tree-based planning -
dc.subject.keywordAuthor interval prediction -
dc.subject.keywordAuthor Motion planning -
dc.subject.keywordPlus ROBUST -
dc.subject.keywordPlus MPC -

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