Bio-Inspired Scan Matching for Efficient Simultaneous Localization and Mapping.

Simultaneous Localization And Mapping (SLAM) is a fundamental problem in robotic systems. In this work, we apply a derivative free bio-inspired techniques to the scan-matching step, which is a the main step in the SLAM problem based on the exploitation of swarm intelligence. For this purpose, we have explore the swarm intelligence optimization meta-heuristics based on the firefly behavior. Aiming at reducing further the translational and rotational scan alignment errors, the proposed scan matching proceeds in two main steps, namely scan-to-scan and scan-to-map matching. The proposed firefly-based implementation of the SLAM provides a good trade-off regarding accuracy and execution efficiency.