Navigation-Aware Guidance in Unknown and GPS-Denied Environments Using the Information Theory
Hyo Sang Shin, Marek Malinowski · Proceedings of International Conference on Intelligent Unmanned Systems · 2014
This paper addresses the guidance and navigation problem of autonomous systems operations in unknown and/or GPS-denied environments. The aim of this paper is to propose an integrated solution to this problem which considers navigation and guidance together based on the information theory to maximise their synergies. The proposed guidance scheme, named as navigation-aware guidance, endeavours to maximise acquired information about environment and vehicle’s position in navigation while optimising guidance objectives. As it’s difficult to utilise the conventional navigation approach, a Simultaneous Localisation and Mapping algorithm is considered as the navigation solution. As it has been shown that the Sparse Extended Information Filter can provide a computationally efficient solution to the SLAM problem, this paper develops a SLAM algorithm using this filter. The performance of the proposed scheme is validated through some numerical simulations.