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Visual Closed-Loop Control for Pouring Liquids
Pouring a specific amount of liquid is a challenging task. In this paper we
develop methods for robots to use visual feedback to perform closed-loop
control for pouring liquids. We propose both a model-based and a model-free
method utilizing deep learning for estimating the volume of liquid in a
container. Our results show that the model-free method is better able to
estimate the volume. We combine this with a simple PID controller to pour
specific amounts of liquid, and show that the robot is able to achieve an
average 38ml deviation from the target amount. To our knowledge, this is the
first use of raw visual feedback to pour liquids in robotics.Comment: To appear at ICRA 201
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