Sensorimotor control of complex, dynamic systems such as humanoids or quadrupedal robots is notoriously difficult. While artificial systems traditionally employ hierarchical …
This work developed a kernel-based residual learning framework for quadrupedal robotic locomotion. Ini-tially, a kernel neural network is trained with data collected from an MPC …
This dissertation addresses the integration of reinforcement learning (RL) with model-based methods to develop robust and efficient bipedal locomotion strategies for robots, highlighting …
The current state-of-the-art in quadruped locomotion is able to produce robust motion for terrain traversal but requires the segmentation of a desired trajectory into a discrete set of …
Oscillatory signals drive reaching and locomotion for both robots and primates. Recent results in neuroscience have shown that periodic signals are present in the motor cortex of …