| Control strategies for soft robotic manipulators: A survey T George Thuruthel, Y Ansari, E Falotico, C Laschi Soft robotics 5 (2), 149-163, 2018 | 568 | 2018 |
| Soft robot perception using embedded soft sensors and recurrent neural networks TG Thuruthel, B Shih, C Laschi, MT Tolley Science Robotics 4 (26), eaav1488, 2019 | 505 | 2019 |
| Electronic skins and machine learning for intelligent soft robots B Shih, D Shah, J Li, TG Thuruthel, YL Park, F Iida, Z Bao, ... Science Robotics 5 (41), 2020 | 431 | 2020 |
| Model-based reinforcement learning for closed-loop dynamic control of soft robotic manipulators TG Thuruthel, E Falotico, F Renda, C Laschi IEEE Transactions on Robotics 35 (1), 124-134, 2018 | 338 | 2018 |
| A review on self-healing polymers for soft robotics S Terryn, J Langenbach, E Roels, J Brancart, C Bakkali-Hassani, ... Materials Today 47, 187-205, 2021 | 199 | 2021 |
| Learning dynamic models for open loop predictive control of soft robotic manipulators TG Thuruthel, E Falotico, F Renda, C Laschi Bioinspiration & biomimetics 12 (6), 066003, 2017 | 141 | 2017 |
| Learning Closed Loop Kinematic Controllers for Continuum Manipulators in Unstructured Environments T George Thuruthel, E Falotico, M Manti, A Pratesi, M Cianchetti, C Laschi Soft Robotics, 285-296, 2017 | 123 | 2017 |
| Stable open loop control of soft robotic manipulators TG Thuruthel, E Falotico, M Manti, C Laschi IEEE Robotics and Automation Letters 3 (2), 1292-1298, 2018 | 86 | 2018 |
| Self-healing ionic gelatin/glycerol hydrogels for strain sensing applications D Hardman, T George Thuruthel, F Iida NPG Asia Materials 14 (1), 11, 2022 | 78 | 2022 |
| Learning global inverse kinematics solutions for a continuum robot TG Thuruthel, E Falotico, M Cianchetti, C Laschi ROMANSY 21-Robot Design, Dynamics and Control: Proceedings of the 21st CISM …, 2016 | 56 | 2016 |
| Improving robotic cooking using batch Bayesian optimization K Junge, J Hughes, TG Thuruthel, F Iida IEEE Robotics and Automation Letters 5 (2), 760-765, 2020 | 53 | 2020 |
| Learning global inverse statics solution for a redundant soft robot TG Thuruthel, E Falotico, M Cianchetti, F Renda, C Laschi Proceedings of the 13th International Conference on Informatics in Control …, 2016 | 49 | 2016 |
| A bistable soft gripper with mechanically embedded sensing and actuation for fast grasping TG Thuruthel, SH Abidi, M Cianchetti, C Laschi, E Falotico 2020 29th IEEE International Conference on Robot and Human Interactive …, 2020 | 47 | 2020 |
| First-order dynamic modeling and control of soft robots T George Thuruthel, F Renda, F Iida Frontiers in Robotics and AI 7, 95, 2020 | 43 | 2020 |
| 3D printable sensorized soft gelatin hydrogel for multi-material soft structures D Hardman, J Hughes, TG Thuruthel, K Gilday, F Iida IEEE Robotics and Automation Letters 6 (3), 5269-5275, 2021 | 25 | 2021 |
| Obstacle avoidance using multi-point potential field approach for an underactuated flat-fish type AUV in dynamic environment S Subramanian, T George, A Thondiyath Trends in Intelligent Robotics, Automation, and Manufacturing: First …, 2012 | 25 | 2012 |
| Using redundant and disjoint time-variant soft robotic sensors for accurate static state estimation TG Thuruthel, J Hughes, A Georgopoulou, F Clemens, F Iida IEEE Robotics and Automation Letters 6 (2), 2099-2105, 2021 | 24 | 2021 |
| Joint entropy-based morphology optimization of soft strain sensor networks for functional robustness TG Thuruthel, J Hughes, F Iida IEEE Sensors Journal 20 (18), 10801-10810, 2020 | 22 | 2020 |
| Cerebellum-inspired approach for adaptive kinematic control of soft robots HT Kalidindi, TG Thuruthel, C Laschi, E Falotico 2019 2nd IEEE International Conference on Soft Robotics (RoboSoft), 684-689, 2019 | 20 | 2019 |
| Closing the control loop with time-variant embedded soft sensors and recurrent neural networks T George Thuruthel, P Gardner, F Iida Soft Robotics 9 (6), 1167-1176, 2022 | 17 | 2022 |
Fumiya IidaUniversity of Cambridge在 cam.ac.uk 的电子邮件经过验证
