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Journal Article

Autonomous Precision Pouring from Unknown Containers

We autonomously pour from unknown symmetric containers found in a typical wet laboratory for the development of a robot-assisted, rapid experiment preparation system. The robot estimates the pouring container symmetric geometry, then leverages simulated pours as priors for a given fluid to pour precisely and quickly in a single attempt. The fluid is detected in the transparent receiving container by combining weight and vision. The change of volume in the receiver is a function of the geometry of the pouring container, the pouring angle, and rate. To determine the volumetric flow rate, the profile for maximum containable volume for a given angle is estimated along with the time delay of the fluid exiting the container. A trapezoidal trajectory generation algorithm prescribes the desired volumetric flow rate as a function of the estimation accuracy. A hybrid control strategy is then used to attenuate volumetric error. Three methods are compared for estimating the volume-angle profile, and it is shown that a combination of online system identification and leveraged model priors results in reliable performance. The major contributions of this work are a system capable of pouring quickly and precisely from varying symmetric containers in a single attempt with limited priors, and a novel fluid detection method. This system is implemented on the Rethink Robotics Sawyer and KUKA LBR iiwa manipulators.

Monroe Kennedy III
Karl Schmeckpeper
Dinesh Thakur
Chenfanfu Jiang
Vijay Kumar
Kostas Daniilidis
IEEE Robotics and Automation Letters
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