Abstract
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.
Highlights
Spinal cord injuries (SCI) can cause paralysis, resulting in minimal motor control and rendering standing and walking impossible
To test the stability of the walking biped in simulation, impulses were applied to the torso (Supplementary Video S1)
It was found that the biped was able to remain stable and continue walking after a maximum impulse of 30 kg·m/s was applied to the back of the torso in the direction of walking as well as after a maximum impulse of 40 kg·m/s was applied to the front of the torso, opposing motion
Summary
Spinal cord injuries (SCI) can cause paralysis, resulting in minimal motor control and rendering standing and walking impossible. Exoskeletons can help patients regain their ability to stand and walk on their own. It has been established previously that combining functional neuromuscular stimulation (FNS) with a powered, lower limb exoskeleton can restore locomotion to such individuals [1,2,3]. There remain many challenges in realizing such systems, given that each patient’s body is unique. One of the primary problems needing more work is the generation of adaptive control systems for stable walking and fall prevention. While much research has been invested in such control for legged robots, there have been few applications of these methods to exoskeletons
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