Teleoperation over distance and through various media such as underwater or in space can result in data loss as well as significant delays.  These impede intuitive operator control of robot manipulators resulting in missed grasps and damage to the robot and the environment.  We are currently investigating methods to quickly learn delay compensation models for individuals and deploy them to increase their performance in delayed telemanipulation.

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