Bayesian optimization for automated model selection G Malkomes, C Schaff, R Garnett Advances in neural information processing systems 29, 2016 | 121 | 2016 |
Jointly learning to construct and control agents using deep reinforcement learning C Schaff, D Yunis, A Chakrabarti, MR Walter 2019 International Conference on Robotics and Automation (ICRA), 9798-9805, 2019 | 81 | 2019 |
Residual policy learning for shared autonomy C Schaff, MR Walter arXiv preprint arXiv:2004.05097, 2020 | 31 | 2020 |
Benchmarking structured policies and policy optimization for real-world dexterous object manipulation N Funk, C Schaff, R Madan, T Yoneda, JU De Jesus, J Watson, ... IEEE Robotics and Automation Letters 7 (1), 478-485, 2021 | 20 | 2021 |
Soft robots learn to crawl: Jointly optimizing design and control with sim-to-real transfer C Schaff, A Sedal, MR Walter arXiv preprint arXiv:2202.04575, 2022 | 13 | 2022 |
Jointly optimizing placement and inference for beacon-based localization C Schaff, D Yunis, A Chakrabarti, MR Walter 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 11 | 2017 |
A robot cluster for reproducible research in dexterous manipulation S Bauer, F Widmaier, M Wüthrich, N Funk, JU De Jesus, J Peters, ... arXiv preprint arXiv:2109.10957, 2021 | 10* | 2021 |
Grasp and motion planning for dexterous manipulation for the real robot challenge T Yoneda, C Schaff, T Maeda, M Walter arXiv preprint arXiv:2101.02842, 2021 | 9 | 2021 |
Neural approaches to co-optimization in robotics C Schaff arXiv preprint arXiv:2209.00579, 2022 | 2 | 2022 |
N-LIMB: Neural Limb Optimization for Efficient Morphological Design C Schaff, MR Walter arXiv preprint arXiv:2207.11773, 2022 | 1 | 2022 |
Sim-to-real transfer of co-optimized soft robot crawlers C Schaff, A Sedal, S Ni, MR Walter Autonomous Robots, 1-17, 2023 | | 2023 |