Publication

Multi-objective cost-to-go functions on robot navigation in dynamic environments

Conference Article

Conference

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Edition

2015

Pages

3824-3829

Doc link

http://dx.doi.org/10.1109/IROS.2015.7353914

File

Download the digital copy of the doc pdf document

Abstract

In our previous work [1] we introduced the Anticipative Kinodynamic Planning (AKP): a robot navigation algorithm in dynamic urban environments that seeks to minimize its disruption to nearby pedestrians. In the present paper, we maintain all the advantages of the AKP, and we overcome the previous limitations by presenting novel contributions to our approach. Firstly, we present a multi-objective cost function to consider different and independent criteria and a well-posed procedure to build a joint cost function in order to select the best path. Then, we improve the construction of the planner tree by introducing a cost-to-go function that will be shown to outperform a classical Euclidean distance approach. In order to achieve real time calculations, we have used a steering heuristic that dramatically speeds up the process. Plenty of simulations and real experiments have been carried out to demonstrate the success of the AKP.

Categories

mobile robots, service robots.

Scientific reference

G. Ferrer and A. Sanfeliu. Multi-objective cost-to-go functions on robot navigation in dynamic environments, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015, Hamburg, Germany, pp. 3824-3829.