Abstract
This work addresses the real time implementation of Simultaneous Localization and Mapping (SLAM). It presents the integration if the Compressed Extended Kalman Filter (CEKF) and a new decorrelation algorithm to reduce the computational and memory requirements of SLAM to ∼ O(N * N a ), being N and N a proportional to the total number of landmark in the global map and local area respectively. It also presents the problematic of outdoors navigation using natural feature based localization methods. The aspect of feature detection and validation is investigated to reliable detect the predominant features in the environment. Experimental results obtained in outdoor environments are presented.
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Guivant, J., Nebot, E. (2003). Implementation of Simultaneous Navigation and Mapping in Large Outdoor Environments. In: Jarvis, R.A., Zelinsky, A. (eds) Robotics Research. Springer Tracts in Advanced Robotics, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36460-9_3
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DOI: https://doi.org/10.1007/3-540-36460-9_3
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