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A Dynamical System-based Approach to Modeling Stable Robot Control Policies via Imitation Learning
Despite tremendous advances in robotics, we are still amazed by the proficiency with which humans perform movements. Even new waves of robotic systems still rely heavily on hardcoded motions with a limited ability to react autonomously and robustly to a dynamically changing environment. This thesis
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