A Benchmarking of DCM Based Architectures for Position and Velocity Controlled Walking of Humanoid Robots
This work addresses locomotion control for humanoid robots, presenting incremental improvements in benchmarking DCM architectures.
The paper tackled the problem of developing and comparing Divergent-Component-of-Motion (DCM) based control architectures for humanoid robot walking, showing that a specific implementation enabled the iCub robot to achieve a walking velocity of 0.41 meters per second.
This paper contributes towards the development and comparison of Divergent-Component-of-Motion (DCM) based control architectures for humanoid robot locomotion. More precisely, we present and compare several DCM based implementations of a three layer control architecture. From top to bottom, these three layers are here called: trajectory optimization, simplified model control, and whole-body QP control. All layers use the DCM concept to generate references for the layer below. For the simplified model control layer, we present and compare both instantaneous and Receding Horizon Control controllers. For the whole-body QP control layer, we present and compare controllers for position and velocity control robots. Experimental results are carried out on the one-meter tall iCub humanoid robot. We show which implementation of the above control architecture allows the robot to achieve a walking velocity of 0.41 meters per second.