ART-Based Fusion of Multi-modal Information for Mobile Robots
- Cite this paper as:
- Berghöfer E., Schulze D., Tscherepanow M., Wachsmuth S. (2011) ART-Based Fusion of Multi-modal Information for Mobile Robots. In: Iliadis L., Jayne C. (eds) Engineering Applications of Neural Networks. IFIP Advances in Information and Communication Technology, vol 363. Springer, Berlin, Heidelberg
Robots operating in complex environments shared with humans are confronted with numerous problems. One important problem is the identification of obstacles and interaction partners. In order to reach this goal, it can be beneficial to use data from multiple available sources, which need to be processed appropriately. Furthermore, such environments are not static. Therefore, the robot needs to learn novel objects. In this paper, we propose a method for learning and identifying obstacles based on multi-modal information. As this approach is based on Adaptive Resonance Theory networks, it is inherently capable of incremental online learning.