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Cataglyphis: An autonomous sample return rover

Yu Gu, Nicholas Ohi, Kyle Lassak, Jared Strader, Lisa Kogan, Alexander Hypes, Scott Harper, Boyi Hu, Matthew Gramlich, Rahul Kavi, Ryan M. Watson, Marvin H. Cheng, Jason N. Gross

Year
2017
Citations
16

Abstract

Abstract This paper presents the design of Cataglyphis, a research rover that won the NASA Sample Return Robot Centennial Challenge in 2015. During the challenge, Cataglyphis was the only robot that was able to autonomously find, retrieve, and return multiple types of samples in a large natural environment without using Earth‐specific sensors such as GPS and magnetic compasses. It navigates through a fusion of measurements collected from inertial sensors, wheel encoders, a nodding Lidar, a set of ranging radios, a camera on a panning platform, and a sun sensor. In addition to visual detection of a homing beacon, computer vision algorithms provide the sample detection, identification, and localization capabilities, with low false positive and false negative rates demonstrated during the competition. The mission planning and control software enables robot behaviors, determines sequences of actions, and helps the robot to recover from various failure conditions. A compliant, under‐actuated manipulator conforms to the natural terrain before picking up samples of various size, weight, and shape.

Keywords

RobotArtificial intelligenceRangingComputer visionComputer scienceInertial measurement unitTerrainGlobal Positioning SystemGeography

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