James Doebbler

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This paper presents an improved Adaptive-Reinforcement Learning Control methodology for the problem of unmanned air vehicle morphing control. The reinforcement learning morphing control function that learns the optimal shape change policy is integrated with an adaptive dynamic inversion control trajectory tracking function. An episodic unsupervised learning(More)
— We are developing a mobile robot capable of emulating general 6-degree-of-freedom spacecraft relative motion. The omni-directional base uses a trio of active split offset castor drive modules to provide smooth, holonomic, precise control of its motion. Encoders measure the rotations of the six wheels and the three castor pivots. We present a generic(More)
—We are developing an autonomous mobile robotic system to emulate six degree of freedom relative spacecraft motion during proximity operations. A mobile omni-directional base robot provides x, y, and yaw planar motion with moderate accuracy through six independently driven motors. With a six degree of freedom micro-positioning Stewart platform on top of the(More)
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