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Chance-Constrained Multilayered Sampling-Based Path Planning for Temporal Logic-Based Missions

Autor: Songhwai Oh, Yoonseon Oh, Kyunghoon Cho, Yunho Choi

Publikováno v: IEEE Transactions on Automatic Control. 66:5816-5829

This paper 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 miss

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c17cf247d8ae3bae9a707acdf73cb83d
https://doi.org/10.1109/tac.2020.3044273

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Hierarchical planning with state abstractions for temporal task specifications

Autor: Yoonseon Oh, Roma Patel, Thao Nguyen, Baichuan Huang, Matthew Berg, Ellie Pavlick, Stefanie Tellex

Publikováno v: Autonomous robots. 46(6)

We often specify tasks for a robot using temporal language that can include different levels of abstraction. For example, the command

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a21953a8f8b27536ce353f09c9ff9000
https://pubmed.ncbi.nlm.nih.gov/35692555

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Online Learning to Approach a Person With No Regret

Autor: Yoonseon Oh, Songhwai Oh, Claire J. Tomlin, Hyemin Ahn, Sungjoon Choi

Publikováno v: IEEE Robotics and Automation Letters. 3:52-59

Each person has a different personal space and behaves differently when another person approaches. Based on this observation, we propose a novel method to learn how to approach a person comfortably based on the person's preference while avoiding unco

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::57b51f42459e6e61988f17848d2e9544
https://doi.org/10.1109/lra.2017.2729783

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Chance-constrained target tracking using sensors with bounded fan-shaped sensing regions

Autor: Songhwai Oh, Yoonseon Oh, Sungjoon Choi

Publikováno v: Autonomous Robots. 42:307-327

We present a robust target tracking algorithm for a mobile robot. It is assumed that a mobile robot carries a sensor with a fan-shaped field of view and finite sensing range. The goal of the proposed tracking algorithm is to minimize the probability

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c886d047a78139f39d722a5df3c4ce2c
https://doi.org/10.1007/s10514-017-9656-7

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Multi-Object Search using Object-Oriented POMDPs

Autor: Nishanth Kumar, Arthur Wandzel, Stefanie Tellex, L S Wong Lawson, Michael D.C. Fishman, Yoonseon Oh

Publikováno v: ICRA

A core capability of robots is to reason about multiple objects under uncertainty. Partially Observable Markov Decision Processes (POMDPs) provide a means of reasoning under uncertainty for sequential decision making, but are computationally intracta

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2160ed1d062c73eccd00798aae980ad6
https://doi.org/10.1109/icra.2019.8793888

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Robust Multi-Objective Path Planning for Flying Robots under Wind Disturbance

Autor: Kyunghoon Cho, Yoonseon Oh, Songhwai Oh

Publikováno v: UR

This paper proposes a robust multi-objective path planning algorithm for flying robots carrying out complex missions. When a robot is put into the field, the robot is required to perform complex missions such as visiting sequential goals. We specify

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2b4b7654cd1e9ac53d5a01d0e1b2ab37
https://doi.org/10.1109/urai.2018.8441822

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Robust multi-layered sampling-based path planning for temporal logic-based missions

Autor: Kyunghoon Cho, Yoonseon Oh, Yunho Choi, Songhwai Oh

Publikováno v: CDC

We investigate a path planning algorithm for generating robust and safe paths, which satisfy mission requirements specified in linear temporal logic (LTL). When robots are deployed to perform a mission, there can be disturbances which can cause missi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::618b8ed754471fc8f5269a121b543381
https://doi.org/10.1109/cdc.2017.8263891

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Multiple-hypothesis chance-constrained target tracking under identity uncertainty

Autor: Songhwai Oh, Yoonseon Oh

Publikováno v: ICRA

We propose a robust target tracking algorithm for a mobile robot under identity uncertainty, which arises in crowded environments. When a mobile robot has a sensor with a fan-shaped field of view and finite sensing region, the proposed algorithm aims

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1a9a40f40a98814104a2bc3308a900d9
https://doi.org/10.1109/icra.2016.7487793

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Pedestrian-following service robot applications using chance-constrained target tracking

Autor: Jinyoung Choi, Songhwai Oh, Yoonseon Oh, Sunwoo Lee

Publikováno v: URAI

This paper presents a mobile robot system where the robot tracks a moving target. The system minimizes the probability of losing the target. If the next position of a moving target has the Gaussian distribution, the proposed system guarantees the tra

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8ba825a07af16ddef4311a6ed3e7021b
https://doi.org/10.1109/urai.2015.7358815

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Chance-constrained target tracking for mobile robots

Autor: Songhwai Oh, Sungjoon Choi, Yoonseon Oh

Publikováno v: ICRA

This paper presents a robust target tracking algorithm for a mobile sensor with a fan-shaped field of view and finite sensing range. The goal of the mobile robot is to track a moving target such that the probability of losing the target is minimized.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3c8bebe7b06bfc8c576a32cd61374b05
https://doi.org/10.1109/icra.2015.7139031

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