A CPG-Based Agile and Versatile Locomotion Framework Using Proximal Symmetry Loss

Understand

Humanoid robots are made to resemble humans but their locomotion abilities are far from ours in terms of agility and versatility.

• When humans walk on complex terrains, or face external disturbances, they combine a set of strategies, unconsciously and efficiently, to regain stability.
• This paper tackles the problem of developing a robust omnidirectional walking framework, which is able to generate versatile and agile locomotion on complex terrains.
• The Linear Inverted Pendulum Model and Central Pattern Generator concepts are used to develop a closed-loop walk engine, which is then combined with a reinforcement learning module.