An Efficient Fast-Mapping SLAM Method for UAS Applications Using Only Range Measurements

Abstract

This paper deals with 3D Simultaneous Localization and Mapping (SLAM), where the UAS uses only range measurements to build a local map of an unknown environment and to self-localize in that map. In the recent years Range Only (RO) SLAM has attracted significant interest, it is suitable for non line-of-sight conditions and bad lighting, being superior to visual SLAM in some problems. However, some issues constrain its applicability in practical cases, such as delays in map building and low map and UAS estimation accuracies. This paper proposes a 3D RO-SLAM scheme for UAS that specifically focuses on improving map building delays and accuracy levels without compromising efficiency in the consumption of resources. The scheme integrates sonar measurements together with range measurements between the robot and beacons deployed in the scenario. The proposed scheme presents two main advantages: (1) it integrates direct range measurements between the robot and the beacons and also range measurements between beacons — called inter-beacon measurements — which significantly reduce map building times and improve map and UAS localization accuracies; and (2) the SLAM scheme is endowed with a supervisory module that self-adapts the measurements that are integrated in SLAM reducing computational, bandwidth and energy consumption. Experimental validation in field experiments with an octorotor UAS showed that the proposed scheme improved map building times in 72%, map accuracy in 40% and UAS localization accuracy in 12%.