Yang, C;
Pu, C;
Xin, G;
Zhang, J;
Li, Z;
(2023)
Learning Complex Motor Skills for Legged Robot Fall Recovery.
IEEE Robotics and Automation Letters
, 8
(7)
pp. 4307-4314.
10.1109/LRA.2023.3281290.
Preview |
Text
Zhibin_Learning_Complex_Motor_Skills_for_Legged_Robot_Fall_Recovery_RAL_Revision.pdf - Accepted Version Download (4MB) | Preview |
Abstract
Falling is inevitable for legged robots in challenging real-world scenarios, where environments are unstructured and situations are unpredictable, such as uneven terrain in the wild. Hence, to recover from falls and achieve all-terrain traversability, it is essential for intelligent robots to possess the complex motor skills required to resume operation. To go beyond the limitation of handcrafted control, we investigated a deep reinforcement learning approach to learn generalized feedback-control policies for fall recovery that are robust to external disturbances. We proposed a design guideline for selecting key states for initialization, including a comparison to the random state initialization. The proposed learning-based pipeline is applicable to different robot models and their corner cases, including both small-/large-size bipeds and quadrupeds. Further, we show that the learned fall recovery policies are hardware-feasible and can be implemented on real robots.
| Type: | Article |
|---|---|
| Title: | Learning Complex Motor Skills for Legged Robot Fall Recovery |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/LRA.2023.3281290 |
| Publisher version: | https://doi.org/10.1109/LRA.2023.3281290 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Machine learning for robot control, reinforcement learning, sensorimotor learning, legged robots |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10175510 |
Archive Staff Only
 |
View Item |
