Cooperative Simultaneous Localization and Mapping in GPS-Denied Environments

Andrey Soloviev, Paul Norris, Chun Yang

Abstract:	This paper discusses the use of feature-aided inertial navigation in Global Positioning System (GPS)-denied environments. Feature-aided techniques are considered for the case of multiple cooperating agents and formulated using cooperative simultaneous localization and mapping (CSLAM). The CSLAM methodology estimates the navigation states of agents (i.e., position, velocity, and attitude) and builds a map of the environment by cooperative processing of agent sensor measurements. The navigation states of each agent are computed by individual aided inertial navigation systems (INS). To reduce drifts in INS navigation outputs, inertial error terms are estimated from the features that are extracted from electro-optical (EO) sensor data including video images and/or ladar scans. The overall system performance is optimized via cooperative multiple-platform feature processing. Specific benefits include increased mapping speed, multi-agent closure of the SLAM loops, multi-agent stereo-vision, multi-agent feature observations for noise averaging, and inter-agent exchange of image depth initialization capabilities that are achieved through motion maneuvers and/or integration of vision and ladar measurements.
Published in:	Proceedings of the 2010 International Technical Meeting of The Institute of Navigation January 25 - 27, 2010 Catamaran Resort Hotel San Diego, CA
Pages:	830 - 838
Cite this article:	Soloviev, Andrey, Norris, Paul, Yang, Chun, "Cooperative Simultaneous Localization and Mapping in GPS-Denied Environments," Proceedings of the 2010 International Technical Meeting of The Institute of Navigation, San Diego, CA, January 2010, pp. 830-838.
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