| Autor: |
Chujun Liu, Andrew G. Lonsberry, Mark J. Nandor, Musa L. Audu, Alexander J. Lonsberry, Roger D. Quinn |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
Biomimetics, Vol 4, Iss 1, p 28 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2313-7673 |
| DOI: |
10.3390/biomimetics4010028 |
| Popis: |
A control system for bipedal walking in the sagittal plane was developed in simulation. The biped model was built based on anthropometric data for a 1.8 m tall male of average build. At the core of the controller is a deep deterministic policy gradient (DDPG) neural network that was trained in GAZEBO, a physics simulator, to predict the ideal foot placement to maintain stable walking despite external disturbances. The complexity of the DDPG network was decreased through carefully selected state variables and a distributed control system. Additional controllers for the hip joints during their stance phases and the ankle joint during toe-off phase help to stabilize the biped during walking. The simulated biped can walk at a steady pace of approximately 1 m/s, and during locomotion it can maintain stability with a 30 kg·m/s impulse applied forward on the torso or a 40 kg·m/s impulse applied rearward. It also maintains stable walking with a 10 kg backpack or a 25 kg front pack. The controller was trained on a 1.8 m tall model, but also stabilizes models 1.4–2.3 m tall with no changes. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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