Returning home after an outward journey is a skill important to the survival of many insects and other animals. Many hymenopterans perform homing navigation using snapshot images taken at specific locations. Snapshot images can be processed in various ways, and this article focuses on the vector model of landmark distribution. In this article, we suggest a new landmark vector model with quantized distance information, and this method is highly successful for navigation without using a reference compass. The landmark distances based on egomotion can be obtained and this information produces a new type of homing navigation with landmark vectors. It includes varying sizes of landmark vectors, depending on the distance. We investigate the effect of quantized distance information or continuous distance in the landmark vectors for homing navigation performance. Even a few classes of discretization of landmark distances and a rough estimation of the current agent location can show excellent homing performance. Our experimental results are compared with those of other conventional navigation algorithms.
Basten, K., & Mallot, H. ( 2010). Simulated visual homing in desert ant natural environments: efficiency of skyline cues. Biological Cybernetics, 102(5), 413-425.
2.
Butz, M., Shirinov, E., & Reif, K. ( 2010). Self-organizing sensorimotor maps plus internal motivations yield animal-like behavior. Adaptive Behavior, 18(3-4), 315-338.
3.
Cartwright, B., & Collett, T. ( 1983). Landmark learning in bees. Journal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology , 151(4), 521-543.
4.
Churchill, D., & Vardy, A. ( 2008). Homing in scale space. In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS2008 (pp. 1307-1312). Nice: IEEE.
5.
Collett, M., & Collett, T. ( 2000). How do insects use path integration for their navigation ? Biological Cybernetics, 83(3), 245-259.
6.
Comaniciu, D., & Meer, P. ( 2002a). Mean shift: A robust approach toward feature space analysis . IEEE Transactions on Pattern Analysis and Machine Intelligence , 24(5), 603-619.
7.
Comaniciu, D., & Meer, P. ( 2002b). Robust analysis of feature spaces: Color image segmentation . In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1997 (pp. 750-755). San Juan: IEEE.
8.
Etienne, A., & Jeffery, K. ( 2004). Path integration in mammals. Hippocampus , 14(2), 180-192.
9.
Etienne, A., Maurer, R., & Sëguinot, V. (1996). Path integration in mammals and its interaction with visual landmarks. Journal of Experimental Biology, 199, 201-209.
10.
Franz, M., Schölkopf, B., Mallot, H., & Bülthoff, H. (1998). Where did I take that snapshot? Scene-based homing by image matching. Biological Cybernetics, 79(3), 191-202.
11.
Goldhoorn, A., Ramisa, A., de Mantaras, R., & Toledo, R. (2007). Using the average landmark vector method for robot homing. Frontiers in artificial intelligence and applications, 163, 331-338.
12.
Graham, P., Philippides, A., & Baddeley, B. ( 2010). Animal cognition: Multi-modal interactions in ant learning . Current Biology, 20(15), R639-R640.
13.
Haferlach, T., Wessnitzer, J., Mangan, M., & Webb, B. ( 2007). Evolving a neural model of insect path integration. Adaptive Behavior, 15(3), 273-287.
Hafner, V., & Möller, R. (2001). Learning of visual navigation strategies. In European Workshop on Learning Robots (EWLR) . Prague: Elsevier.
16.
Labrosse, F. ( 2006). The visual compass: performance and limitations of an appearance-based method. Journal of Field Robotics, 23(10), 913-941.
17.
Lambrinos, D., Moller, R., Labhart, T., Pfeifer, R., & Wehner, R. ( 2000). A mobile robot employing insect strategies for navigation . Robotics and Autonomous Systems, 30(1-2), 39-64.
18.
Luschi, P., Papi, F., Liew, H., Chan, E., & Bonadonna, F. ( 1996). Long-distance migration and homing after displacement in the green turtle (Chelonia mydas): a satellite tracking study. Journal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology, 178(4), 447-452.
19.
Mather, J. ( 1991). Navigation by spatial memory and use of visual landmarks in octopuses. Journal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology, 168(4), 491-497.
20.
Mittelstaedt, M., & Mittelstaedt, H. (1980). Homing by path integration in a mammal. Naturwissenschaften, 67(11), 566-567.
21.
Möller, R. ( 2000). Insect visual homing strategies in a robot with analog processing. Biological Cybernetics, 83(3), 231-243.
22.
Möller, R. ( 2001). Do insects use templates or parameters for landmark navigation ? Journal of Theoretical Biology, 210(1), 33-45.
23.
Möller, R. ( 2009). Local visual homing by warping of two-dimensional images . Robotics and Autonomous Systems, 57(1), 87-101.
24.
Möller, R., & Vardy, A. ( 2006). Local visual homing by matched-filter descent in image distances. Biological Cybernetics, 95(5), 413-430.
25.
O’Keefe, J., & Burgess, N. ( 1996). Geometric determinants of the place fields of hippocampal neurons. Nature, 381(6581), 425-428.
26.
Smith, L., Philippides, A., Graham, P., Baddeley, B., & Husbands, P. ( 2007). Linked local navigation for visual route guidance. Adaptive Behavior, 15(3), 257-271.
27.
Stürzl, W., & Zeil, J. ( 2007). Depth, contrast and view-based homing in outdoor scenes . Biological Cybernetics, 96(5), 519-531.
28.
Touretzky, D., & Redish, A. ( 1996). Theory of rodent navigation based on interacting representations of space. Hippocampus, 6(3), 247-270.
29.
Trullier, O., & Meyer, J. ( 2000). Animat navigation using a cognitive graph. Biological Cybernetics, 83(3), 271-285.
30.
Vardy, A., & Möller, R. (2005). Biologically plausible visual homing methods based on optical flow techniques. Connection Science, 17(1), 47-89.
31.
Webb, B. ( 2009). Animals versus animats: Or why not model the real iguana?Adaptive Behavior, 17(4), 269-286.
32.
Wehner, R., Michel, B., & Antonsen, P. ( 1996). Visual navigation in insects: coupling of egocentric and geocentric information. Journal of Experimental Biology , 199, 129-140.
33.
Wei, R., Austin, D., & Mahony, R. ( 2005). Biomimetic application of desert ant visual navigation for mobile robot docking with weighted landmarks. International Journal of Intelligent Systems Technologies and Applications, 1(1), 174-190.
34.
Yamauchi, B., Schultz, A., & Adams, W. ( 1999). Integrating exploration and localization for mobile robots . Adaptive Behavior, 7(2), 217-248.
35.
Yu, S.-E., & Kim, D. ( 2010a). Discretized landmark distance estimation method for mobile robot navigation. In Korea Robotics Society Annual Conference 2010 (pp. 136-137). Jeonju: Korea Robotics Society.
36.
Yu, S.-E., & Kim, D. ( 2010b). Distance estimation method with snapshot landmark images in the robotic homing navigation. In The 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 275-280). Taipei: Korea Robotics Society.
37.
Zeil, J., & Hemmi, J. ( 2006). The visual ecology of fiddler crabs. Journal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology, 192(1), 1-25.
38.
Zeil, J., Hofmann, M., & Chahl, J. ( 2003). Catchment areas of panoramic snapshots in outdoor scenes . Journal of the Optical society of America A, 20(3), 450-469.
