Algorithm of Particle Data Association for SLAM Based on Improved Ant Algorithm

Nauka i Obrazovanie

KeKe Gen¹  N. A. Chulin¹ 

[1] Bauman Moscow State Technical University;

关键词: algorithm SLAM;    chaotic disturbance;    improved ant algorithm;    Mahalanobis distance;    Euclidean distance;   

DOI  :  10.7463/1015.0818707

来源: DOAJ

【 摘 要 】

The article considers a problem of data association algorithm for simultaneous localization and mapping guidelines in determining the route of unmanned aerial vehicles (UAVs). Currently, these equipments are already widely used, but mainly controlled from the remote operator. An urgent task is to develop a control system that allows for autonomous flight. Algorithm SLAM (simultaneous localization and mapping), which allows to predict the location, speed, the ratio of flight parameters and the coordinates of landmarks and obstacles in an unknown environment, is one of the key technologies to achieve real autonomous UAV flight. The aim of this work is to study the possibility of solving this problem by using an improved ant algorithm.

The data association for SLAM algorithm is meant to establish a matching set of observed landmarks and landmarks in the state vector. Ant algorithm is one of the widely used optimization algorithms with positive feedback and the ability to search in parallel, so the algorithm is suitable for solving the problem of data association for SLAM. But the traditional ant algorithm in the process of finding routes easily falls into local optimum. Adding random perturbations in the process of updating the global pheromone to avoid local optima. Setting limits pheromone on the route can increase the search space with a reasonable amount of calculations for finding the optimal route.

The paper proposes an algorithm of the local data association for SLAM algorithm based on an improved ant algorithm. To increase the speed of calculation, local data association is used instead of the global data association. The first stage of the algorithm defines targets in the matching space and the observed landmarks with the possibility of association by the criterion of individual compatibility (IC). The second stage defines the matched landmarks and their coordinates using improved ant algorithm. Simulation results confirm the efficiency and effectiveness of the algorithm.

【 授权许可】

Unknown