Grid map establishment and target tracking based on adaptive multi-feature matching method

In this paper, we present an adaptive multi-feature matching method for target detection and target tracking based on an occupancy grid map in dynamic outdoor environments on a moving vehicle equipped with laser radar. The raw scanning points are divided into blocks and the matching strategy of ICP (Iterated Closest Points) algorithm is modified by using the multi-feature information of objects. We introduce a method to adaptively correct the weighting coefficients of the multi-feature in the similarity function. After matching the objects in the two adjacent frames, the online grid map is updated by Bayesian theory and the probability of inverse sensor model. The moving objects are detected with grid map matching. Then, the moving targets are finally tracked by tracker management coupled with Kalman filter. In the experiment, the online grid map is established and the stable results for targets tracking are also achieved.