Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 오윤선 | - |
dc.date.accessioned | 2022-09-28T06:04:28Z | - |
dc.date.available | 2022-09-28T06:04:28Z | - |
dc.date.issued | 2020-12 | - |
dc.identifier.citation | IEEE TRANSACTIONS ON AUTOMATIC CONTROL, v. 66, no. 12, page. 5816-5829 | en_US |
dc.identifier.issn | 0018-9286; 1558-2523 | en_US |
dc.identifier.uri | https://ieeexplore.ieee.org/document/9293004 | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/175005 | - |
dc.description.abstract | This article introduces a robust and safe path planning algorithm in order to satisfy mission requirements specified in linear temporal logic (LTL). When a path is planned to accomplish a mission, it is possible for a robot to fail to complete the mission or collide with obstacles due to noises and disturbances in the system. Hence, we need to find a robust path against possible disturbances. We introduce a robust path planning algorithm, which maximizes the probability of success in accomplishing a given mission by considering disturbances, while minimizing the moving distance of a robot. The proposed method can guarantee the safety of the planned trajectory by incorporating an LTL formula and chance constraints in a hierarchical manner. A high-level planner generates a discrete plan satisfying the mission requirements specified in LTL. A low-level planner builds a sampling-based rapidly exploring random tree search tree to minimize both the mission failure probability and the moving distance while guaranteeing the probability of collision with obstacles to be below a specified threshold. We have analyzed properties of the proposed algorithm theoretically and validated the robustness and safety of paths generated by the algorithm in simulation and experiments using a quadrotor. | en_US |
dc.description.sponsorship | This work was supported in part by the Institute of Information and Communications Technology Planning and Evaluation (IITP) grant funded by the Korea government (MSIT) under Grant 2019-0-01309 (Development of AI Technology for Guidance of a Mobile Robot to its Goal with Uncertain Maps in Indoor/Outdoor Environments). | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | en_US |
dc.subject | Linear temporal logic (LTL); path planning; probabilistic guarantee | en_US |
dc.title | Chance-Constrained Multilayered Sampling-Based Path Planning for Temporal Logic-Based Missions | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/TAC.2020.3044273 | en_US |
dc.relation.journal | IEEE TRANSACTIONS ON AUTOMATIC CONTROL | - |
dc.contributor.googleauthor | Oh, Yoonseon | - |
dc.contributor.googleauthor | Cho, Kyunghoon | - |
dc.contributor.googleauthor | Choi, Yunho | - |
dc.contributor.googleauthor | Oh, Songhwai | - |
dc.relation.code | 2020047938 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | SCHOOL OF ELECTRONIC ENGINEERING | - |
dc.identifier.pid | yoh21 | - |
dc.identifier.orcid | https://orcid.org/0000-0002-1689-231X | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.