| Preference-based learning for exoskeleton gait optimization M Tucker, E Novoseller, C Kann, Y Sui, Y Yue, JW Burdick, AD Ames 2020 IEEE international conference on robotics and automation (ICRA), 2351-2357, 2020 | 88 | 2020 |
| A review of current state-of-the-art control methods for lower-limb powered prostheses R Gehlhar, M Tucker, AJ Young, AD Ames Annual Reviews in Control, 2023 | 35 | 2023 |
| Roial: Region of interest active learning for characterizing exoskeleton gait preference landscapes K Li, M Tucker, E Bıyık, E Novoseller, JW Burdick, Y Sui, D Sadigh, Y Yue, ... 2021 IEEE International Conference on Robotics and Automation (ICRA), 3212-3218, 2021 | 35 | 2021 |
| Towards variable assistance for lower body exoskeletons T Gurriet, M Tucker, A Duburcq, G Boeris, AD Ames IEEE Robotics and Automation Letters 5 (1), 266-273, 2019 | 33 | 2019 |
| Human preference-based learning for high-dimensional optimization of exoskeleton walking gaits M Tucker, M Cheng, E Novoseller, R Cheng, Y Yue, JW Burdick, AD Ames 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 32 | 2020 |
| Preference-based learning for user-guided hzd gait generation on bipedal walking robots M Tucker, N Csomay-Shanklin, WL Ma, AD Ames 2021 IEEE International Conference on Robotics and Automation (ICRA), 2804-2810, 2021 | 24 | 2021 |
| Safety-aware preference-based learning for safety-critical control R Cosner, M Tucker, A Taylor, K Li, T Molnar, W Ubelacker, A Alan, ... Learning for Dynamics and Control Conference, 1020-1033, 2022 | 21 | 2022 |
| Evaluation of safety and performance of the self balancing walking system Atalante in patients with complete motor spinal cord injury J Kerdraon, JG Previnaire, M Tucker, P Coignard, W Allegre, E Knappen, ... Spinal Cord Series and Cases 7 (1), 1-8, 2021 | 14 | 2021 |
| Natural multicontact walking for robotic assistive devices via musculoskeletal models and hybrid zero dynamics K Li, M Tucker, R Gehlhar, Y Yue, AD Ames IEEE Robotics and Automation Letters 7 (2), 4283-4290, 2022 | 10 | 2022 |
| Learning controller gains on bipedal walking robots via user preferences N Csomay-Shanklin, M Tucker, M Dai, J Reher, AD Ames 2022 International Conference on Robotics and Automation (ICRA), 10405-10411, 2022 | 9 | 2022 |
| Input-to-state stability in probability P Culbertson, RK Cosner, M Tucker, AD Ames 2023 62nd IEEE Conference on Decision and Control (CDC), 5796-5803, 2023 | 5 | 2023 |
| Polar: Preference optimization and learning algorithms for robotics M Tucker, K Li, Y Yue, AD Ames arXiv preprint arXiv:2208.04404, 2022 | 5 | 2022 |
| Robust bipedal locomotion: Leveraging saltation matrices for gait optimization M Tucker, N Csomay-Shanklin, AD Ames 2023 IEEE International Conference on Robotics and Automation (ICRA), 12218 …, 2023 | 4 | 2023 |
| Stabilization of exoskeletons through active ankle compensation T Gurriet, M Tucker, C Kann, G Boeris, AD Ames arXiv preprint arXiv:1909.11848, 2019 | 4 | 2019 |
| An input-to-state stability perspective on robust locomotion M Tucker, AD Ames IEEE Control Systems Letters, 2023 | 3 | 2023 |
| Leveraging user preference in the design and evaluation of lower-limb exoskeletons and prostheses KA Ingraham, M Tucker, AD Ames, EJ Rouse, MK Shepherd Current Opinion in Biomedical Engineering, 100487, 2023 | 2 | 2023 |
| Humanoid Robot Co-Design: Coupling Hardware Design with Gait Generation via Hybrid Zero Dynamics AB Ghansah, J Kim, M Tucker, AD Ames 2023 62nd IEEE Conference on Decision and Control (CDC), 1879-1885, 2023 | 1 | 2023 |
| Synthesizing Robust Walking Gaits via Discrete-Time Barrier Functions with Application to Multi-Contact Exoskeleton Locomotion M Tucker, K Li, AD Ames arXiv preprint arXiv:2310.06169, 2023 | | 2023 |
| Preferential Multi-Attribute Bayesian Optimization with Application to Exoskeleton Personalization R Astudillo, K Li, M Tucker, CX Cheng, A Ames, Y Yue ICML 2023 Workshop The Many Facets of Preference-Based Learning, 2023 | | 2023 |
| Enabling Robust and User-Customized Bipedal Locomotion on Lower-Body Assistive Devices via Hybrid System Theory and Preference-Based Learning M Tucker California Institute of Technology, 2023 | | 2023 |
Aaron D. AmesBren Professor, Mechanical and Civil Engineering, Control and Dynamical Systems, CaltechAdresse e-mail validée de cds.caltech.edu
