S Koseki, M Hayashibe, D Owaki - PLOS Computational Biology, 2024 - journals.plos.org
Humans can generate and sustain a wide range of walking velocities while optimizing their energy efficiency. Understanding the intricate mechanisms governing human walking will …
In this research, an optimization methodology was introduced for improving bipedal robot locomotion controlled by reinforcement learning (RL) algorithms. Specifically, the study …
Humans have many redundancies in their bodies and can make effective use of them to adapt to changes in the environment while walking. They can also vary their walking speed …
In this research, Deep Reinforcement Learning (DRL) is employed to develop an ankle controller for a passive biped walker with round feet. The selected DRL technique is Soft …
The use of parallel elastic actuators provides additional torques in bipedal robots. However due to existing constraints like available power or joint's range of motion, optimal actuators …