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Collaborative localization of aerial and ground robots through elevation maps


Kasllin, Roman; Fankhauser, Peter; Stumm, Elena; Taylor, Zachary; Müggler, Elias; Delmerico, Jeffrey; Scaramuzza, Davide; Siegwart, Roland; Hutter, Marco (2016). Collaborative localization of aerial and ground robots through elevation maps. In: International Symposium on Safety, Security, and Rescue Robotics (SSRR), Lausanne, 2016., Lausanne, Switzerland, 23 October 2016 - 27 October 2016, 1-7.

Abstract

Collaboration between aerial and ground robots can benefit from exploiting the complementary capabilities of each system, thereby improving situational awareness and environment interaction. For this purpose, we present a localization method that allows the ground robot to determine and track its position within a map acquired by a flying robot. To maintain invariance with respect to differing sensor choices and viewpoints, the method utilizes elevation maps built independently by each robot’s onboard sensors. The elevation maps are then used for global localization: specifically, we find the relative position and orientation of the ground robot using the aerial map as a reference. Our work compares four different similarity measures for computing the congruence of
elevation maps (akin to dense, image-based template matching) and evaluates their merit. Furthermore, a particle filter is
implemented for each similarity measure to track multiple location hypotheses and to use the robot motion to converge to a unique solution. This allows the ground robot to make use of the extended coverage of the map from the flying robot. The presented method is demonstrated through the collaboration of a quadrotor equipped with a downward-facing monocular camera and a walking robot equipped with a rotating laser range scanner.

Abstract

Collaboration between aerial and ground robots can benefit from exploiting the complementary capabilities of each system, thereby improving situational awareness and environment interaction. For this purpose, we present a localization method that allows the ground robot to determine and track its position within a map acquired by a flying robot. To maintain invariance with respect to differing sensor choices and viewpoints, the method utilizes elevation maps built independently by each robot’s onboard sensors. The elevation maps are then used for global localization: specifically, we find the relative position and orientation of the ground robot using the aerial map as a reference. Our work compares four different similarity measures for computing the congruence of
elevation maps (akin to dense, image-based template matching) and evaluates their merit. Furthermore, a particle filter is
implemented for each similarity measure to track multiple location hypotheses and to use the robot motion to converge to a unique solution. This allows the ground robot to make use of the extended coverage of the map from the flying robot. The presented method is demonstrated through the collaboration of a quadrotor equipped with a downward-facing monocular camera and a walking robot equipped with a rotating laser range scanner.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:27 October 2016
Deposited On:24 Nov 2016 15:07
Last Modified:29 Aug 2017 16:45
Publisher:IEEE
Free access at:Related URL. An embargo period may apply.
Official URL:http://rpg.ifi.uzh.ch/docs/SSRR16_Kaeslin.pdf
Related URLs:http://rpg.ifi.uzh.ch/docs/SSRR16_Kaeslin.pdf (Author)
http://ssrrobotics.org/ (Organisation)
Other Identification Number:merlin-id:14065

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