The MattLab is developing the intelligence necessary to enable complex platforms to autonomously interact with and perform meaningful work in complex environments. The task areas include biologically inspired dynamic locomotion and learning, compliant manipulation for agriculture and food preparation, managing uncertainty in human-robot interaction, and field-ready search and rescue robotics. The central ideas that drive this work are classical control theory, Bayesian inference, practical optimal control, and modern reinforcement learning.
