Deep reinforcement learning of navigation in a complex and crowded environment with a limited field of view J Choi, K Park, M Kim, S Seok 2019 International Conference on Robotics and Automation (ICRA), 5993-6000, 2019 | 67 | 2019 |
Multi-focus attention network for efficient deep reinforcement learning J Choi, BJ Lee, BT Zhang Workshops at the thirty-first AAAI conference on artificial intelligence, 2017 | 51 | 2017 |
Robust human following by deep bayesian trajectory prediction for home service robots BJ Lee, J Choi, C Baek, BT Zhang 2018 IEEE international conference on robotics and automation (ICRA), 7189-7195, 2018 | 39 | 2018 |
Human body orientation estimation using convolutional neural network J Choi, BJ Lee, BT Zhang arXiv preprint arXiv:1609.01984, 2016 | 39 | 2016 |
Risk-conditioned distributional soft actor-critic for risk-sensitive navigation J Choi, C Dance, JE Kim, S Hwang, K Park 2021 IEEE International Conference on Robotics and Automation (ICRA), 8337-8344, 2021 | 19 | 2021 |
Fast adaptation of deep reinforcement learning-based navigation skills to human preference J Choi, C Dance, J Kim, K Park, J Han, J Seo, M Kim 2020 IEEE International Conference on Robotics and Automation (ICRA), 3363-3370, 2020 | 17 | 2020 |
Perception-action-learning system for mobile social-service robots using deep learning BJ Lee, J Choi, CY Lee, KW Park, S Choi, C Han, DS Han, C Baek, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 14 | 2018 |
Micro-objective learning: Accelerating deep reinforcement learning through the discovery of continuous subgoals S Lee, SW Lee, J Choi, DH Kwak, BT Zhang arXiv preprint arXiv:1703.03933, 2017 | 3 | 2017 |
Method and system for training autonomous driving agent on basis of deep reinforcement learning J Choi, P Kay, M Kim, S Sangok, SEO Joonho US Patent App. 17/466,450, 2021 | 2 | 2021 |
Method and system for determining action of device for given state using model trained based on risk-measure parameter J Choi, CR Dance, JE Kim, S Hwang, P Kay US Patent App. 17/518,695, 2022 | 1 | 2022 |
Pedestrian-following service robot applications using chance-constrained target tracking J Choi, S Lee, Y Oh, S Oh 2015 12th International Conference on Ubiquitous Robots and Ambient …, 2015 | 1 | 2015 |
Method and system for controlling a plurality of robots traveling through a specific area, and building in which robots are disposed Y Younghwan, P Kay, JY Kim, J Choi, JE Kim US Patent App. 18/502,757, 2024 | | 2024 |
Method and system for remotely controlling robots, and building having traveling robots flexibly responding to obstacles YH Yoon, P Kay, JY Choi, JE Kim, SB Hwang US Patent App. 18/469,269, 2024 | | 2024 |
Method and system for optimizing reinforcement-learning-based autonomous driving according to user preferences J Choi, JE Kim, P Kay, HAN Jaehun, SEO Joonho, M Kim, C Dance US Patent App. 17/657,878, 2022 | | 2022 |
변분 베이지안 예측법 기반의 홈 서비스 로봇의 자연스러운 사람 따라다니기 기술 이범진, 최진영, 장병탁 한국정보과학회 학술발표논문집, 791-793, 2018 | | 2018 |
Deep Learning Methods for Perception and Navigation of Service Robots 최진영 서울대학교 대학원, 2018 | | 2018 |
다중 에이전트의 효율적인 행동을 위한 마스터-슬레이브 정책 네트워크 김기범, 김은솔, 최진영, 장병탁 한국정보과학회 학술발표논문집, 942-944, 2017 | | 2017 |
소셜 서비스 로봇을 위한 딥러닝 기반의 통합 인지 프레임워크 구현 및 로봇의 행동 메커니즘 설계 이범진, 최진영, 이충연, 박경화, 백다솜, 최성준, 한철호, 한동식, ... 로봇과 인간 14 (4), 9-16, 2017 | | 2017 |
주의 집중 통신을 사용한 다중 에이전트 딥 강화학습 최진영, 이범진, 장병탁 한국정보과학회 학술발표논문집, 817-819, 2017 | | 2017 |
다중 초점 주의 집중 네트워크를 사용한 딥 강화학습 최진영, 이범진, 장병탁 한국정보과학회 학술발표논문집, 675-677, 2016 | | 2016 |