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Recently, end-to-end learning frameworks are gaining prevalence in the field of robot control. These frameworks input states/images and directly predict the torques or the action parameters. However, these approaches are often critiqued due to their huge data requirements for learning a task. The argument of the difficulty in scalability to multiple tasks is well founded, since training these tasks...
This paper presents the control strategy and efficient tasks for training with ReachMAN, a compact, portable 3 degree-of-freedom robot to train reaching, pronosupination and grasping, independently or in combination. A pilot study was performed with three sub-acute patients to evaluate the potential use of ReachMAN as a rehabilitation tool, and determine how it should be used. All subjects improved...
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