Visual Memory Update for Life-Long Mobile Robot Navigation
A central clue for implementation of visual memory based navigation strategies relies on efficient point matching between the current image and the key images of the memory. However, the visual memory may become out of date after some times because the appearance of real-world environments keeps changing. It is thus necessary to remove obsolete information and to add new data to the visual memory over time. In this paper, we propose a method based on short-term and long term memory concepts to update the visual memory of mobile robots during navigation. The results of our experiments show that using this method improves the robustness of the localization and path-following steps.
KeywordsVisual memory life-long mapping mobile robots
Unable to display preview. Download preview PDF.
- 1.Royer, E., Lhuillier, M., Dhome, M., Lavest, J.-M.: Monocular vision for mobile robot localization and autonomous navigation. International Journal of Computer Vision, Special Joint Issue on Vision and Robotics 74, 237–260 (2007)Google Scholar
- 2.Yamauchi, B., Langley, P.: Spatial learning for navigation in dynamic environments. IEEE Transactions on Systems, Man and Cybernetics 26(3), 496–505 (1997)Google Scholar
- 5.Atkinson, R., Shiffrin, R.: Human memory: a Proposed System and its Control Processes. In: Spence, K.W., Spence, J.T. (eds.) The Psychology of Learning and Motivation. Academic Press, New York (1968)Google Scholar
- 6.Courbon, J., Mezouar, Y., Martinet, P.: Autonomous navigation of vehicles from a visual memory using a generic camera model. Intelligent Transport System (ITS) 10, 392–402 (2009)Google Scholar