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Learning visual servo policies via planner cloning
Learning control policies for visual servoing in novel environments is an important problem.
Adapting control policies from simulation to reality using a pairwise loss
This paper proposes an approach to domain transfer based on a pairwise loss function that helps transfer control policies learned in simulation onto a real robot.
Learning a visuomotor controller for real world robotic grasping using simulated depth images
This paper proposes an approach to learning a closed-loop controller for robotic grasping that dynamically guides the gripper to the object.
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