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Proceedings Paper

R-MASTIF: robotic mobile autonomous system for threat interrogation and object fetch
Author(s): Aveek Das; Dinesh Thakur; James Keller; Sujit Kuthirummal; Zsolt Kira; Mihail Pivtoraiko
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Paper Abstract

Autonomous robotic “fetch” operation, where a robot is shown a novel object and then asked to locate it in the field, re- trieve it and bring it back to the human operator, is a challenging problem that is of interest to the military. The CANINE competition presented a forum for several research teams to tackle this challenge using state of the art in robotics technol- ogy. The SRI-UPenn team fielded a modified Segway RMP 200 robot with multiple cameras and lidars. We implemented a unique computer vision based approach for textureless colored object training and detection to robustly locate previ- ously unseen objects out to 15 meters on moderately flat terrain. We integrated SRI’s state of the art Visual Odometry for GPS-denied localization on our robot platform. We also designed a unique scooping mechanism which allowed retrieval of up to basketball sized objects with a reciprocating four-bar linkage mechanism. Further, all software, including a novel target localization and exploration algorithm was developed using ROS (Robot Operating System) which is open source and well adopted by the robotics community. We present a description of the system, our key technical contributions and experimental results.

Paper Details

Date Published: 4 February 2013
PDF: 9 pages
Proc. SPIE 8662, Intelligent Robots and Computer Vision XXX: Algorithms and Techniques, 86620O (4 February 2013); doi: 10.1117/12.2010720
Show Author Affiliations
Aveek Das, SRI International Sarnoff (United States)
Dinesh Thakur, Univ. of Pennsylvania (United States)
James Keller, Univ. of Pennsylvania (United States)
Sujit Kuthirummal, SRI International Sarnoff (United States)
Zsolt Kira, SRI International Sarnoff (United States)
Mihail Pivtoraiko, Univ. of Pennsylvania (United States)

Published in SPIE Proceedings Vol. 8662:
Intelligent Robots and Computer Vision XXX: Algorithms and Techniques
Juha Röning; David Casasent, Editor(s)

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