Cooperative Consensus Simultaneous Localization And Mapping For Multi Blimp System

• Main Author: Kadir, Herdawatie Abdul
• Format: Thesis
• Language: English
• Published: 2017
• Subjects: T Technology; TK Electrical Engineering. Electronics. Nuclear Engineering
• Online Access: http://eprints.usm.my/45937/1/Cooperative%20Consensus%20Simultaneous%20Localization%20And%20Mapping%20For%20Multi%20Blimp%20System.pdf; http://eprints.usm.my/45937/

Navigation in an ocean environment with few static features and dynamic water background is an adventurous field to be explored by multi-agent system. This is because of its non-uniform availability of measurement on the ocean surface since the spatial feature distribution is greatly varied. Thus, it is desirable to design a cooperative localisation and mapping framework that is capable to handle spurious detection, reduce the localisation uncertainty of an agent and achieve fast and good decision. The main objective of this research is to design a cooperative simultaneous localisation and mapping method for multi blimp system involving the dynamic water surface as the background and small flock consensus as the group decision method. A new cooperative framework for the multi blimp system consisting of three blimps and buoys was developed and designed for this purpose. The simultaneous localisation and mapping were designed by integrating three methods which are the Extended Kalman Filter, the enhanced Scale Invariant Feature Transform and Received Signal Strength Indicator to improve the data association process. The group perception of direction based on small flock of animal consensus was taken into the data association process. It was discovered that this cooperative consensus simultaneous localisation and mapping was able to reduce the number of feature points and detect the desired features in clear and dark water environments. In addition, based on cooperative consensus benchmarking, this method was able to achieve faster consensus to up to 8.3 % and 42 % than the scale free model and klemm-eguilez model respectively. On top of these, its heading accuracy was found to be more accurate to up to 30 % and 76 % than the scale free model and klemm-eguilez model respectively. Overall, the proposed approach has achieved its prominent results and it is proven to be significantly reliable and applicable to be implemented in the ocean observation monitoring system.