Physics-Based Simulation and Machine Learning Tool Box for Fast and Robust Training of a Powered Upper Extremity Exoskeleton

Human-worn powered exoskeleton robots can provide extensive benefits to the USAF, the DoD, as well as the commercial and industrial sectors in efficiently and effectively performing tasks such as: loading and unloading boxes/crates and equipment; loading munitions; assembling pallets; and in many other applications. The benefit of exoskeleton robots can be multiplied by allowing these to learn from their operators how to execute tasks and then allowing these robots to perform these tasks on their own operating under supervised autonomy (man-on-the-loop). Phase I of this effort aims to assess the applicability of physics-based simulation and Machine Learning (ML) tools tailored to rapidly allow exoskeleton robots to learn, from their operators, how to perform a collection of USAF relevant tasks, and how to integrate this new capability into the customers and end-users work flow.