An inverse optimal control approach to explain human arm reaching control based on multiple internal models OS Oguz, Z Zhou, S Glasauer, D Wollherr Scientific reports 8 (1), 5583, 2018 | 29 | 2018 |
A general framework to increase safety of learning algorithms for dynamical systems based on region of attraction estimation Z Zhou, OS Oguz, M Leibold, M Buss IEEE Transactions on Robotics 36 (5), 1472-1490, 2020 | 20 | 2020 |
A hybrid framework for understanding and predicting human reaching motions OS Oguz, Z Zhou, D Wollherr Frontiers in Robotics and AI 5, 27, 2018 | 17 | 2018 |
Learning a Low-dimensional Representation of a Safe Region for Safe Reinforcement Learning on Dynamical Systems Z Zhou, OS Oguz, M Leibold, M Buss IEEE Transactions on Neural Networks and Learning Systems, 2021 | 14 | 2021 |
ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planning Z Zhou, J Song, K Yao, Z Shu, L Ma 2024 IEEE International Conference on Robotics and Automation (ICRA), 2023 | 12* | 2023 |
Hybrid human motion prediction for action selection within human-robot collaboration OS Oguz, V Gabler, G Huber, Z Zhou, D Wollherr 2016 International Symposium on Experimental Robotics, 289-298, 2017 | 12 | 2017 |
Self-refined large language model as automated reward function designer for deep reinforcement learning in robotics J Song, Z Zhou, J Liu, C Fang, Z Shu, L Ma arXiv preprint arXiv:2309.06687, 2023 | 9 | 2023 |
Off-policy risk-sensitive reinforcement learning-based constrained robust optimal control C Li, Q Liu, Z Zhou, M Buss, F Liu IEEE Transactions on Systems, Man, and Cybernetics: Systems 53 (4), 2478-2491, 2022 | 8* | 2022 |
Guided Sequential Manipulation Planning Using a Hierarchical Policy HM Van, OS Oguz, Z Zhou, M Toussaint RSS Learning in Task and Motion Planning Workshop, 2020 | 6 | 2020 |
Mosaic: Model-based Safety Analysis Framework for AI-enabled Cyber-Physical Systems X Xie, J Song, Z Zhou, F Zhang, L Ma arXiv preprint arXiv:2305.03882, 2023 | 3 | 2023 |
Towards building ai-cps with nvidia isaac sim: An industrial benchmark and case study for robotics manipulation Z Zhou, J Song, X Xie, Z Shu, L Ma, D Liu, J Yin, S See Proceedings of the 46th International Conference on Software Engineering …, 2024 | 2 | 2024 |
Data generation method for learning a low-dimensional safe region in safe reinforcement learning Z Zhou, OS Oguz, Y Ren, M Leibold, M Buss arXiv preprint arXiv:2109.05077, 2021 | 2 | 2021 |
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward X Xie, J Song, Z Zhou, Y Huang, D Song, L Ma arXiv preprint arXiv:2404.08517, 2024 | 1 | 2024 |
GenSafe: A Generalizable Safety Enhancer for Safe Reinforcement Learning Algorithms Based on Reduced Order Markov Decision Process Model Z Zhou, X Xie, J Song, Z Shu, L Ma arXiv preprint arXiv:2406.03912, 2024 | | 2024 |
Enabling Versatility and Dexterity of the Dual-Arm Manipulators: A General Framework Toward Universal Cooperative Manipulation Y Ren, Z Zhou, Z Xu, Y Yang, G Zhai, M Leibold, F Ni, Z Zhang, M Buss, ... IEEE Transactions on Robotics, 2024 | | 2024 |
Safe Reinforcement Learning Methods for Complex Dynamical Systems Based on Model Order Reduction Techniques Z Zhou Technische Universität München, 2022 | | 2022 |