The concept of affordances, introduced in psychology by J. J. Gibson, has recently attracted interest in the development of cognitive systems in autonomous robotics. In earlier work (Sahin, Çakmak, Dogar, Ugur, & Üçoluk), we reviewed the uses of this concept in different fields and proposed a formalism to use affordances at different levels of robot control. In this article, we first review studies in ecological psychology on the learning and perception of traversability in organisms and describe how the existence of traversability was judged to exist. We then describe the implementation of one part of the affordance formalism for the learning and perception of traversability affordances on a mobile robot equipped with range sensing ability. Through experiments inspired by ecological psychology, we show that the robot, by interacting with its environment, can learn to perceive the traversability affordances. Moreover, we claim that three of the main attributes that are commonly associated with affordances, that is, affordances being relative to the environment, providing perceptual economy, and providing general information, are simply consequences of learning from the interactions of the robot with the environment.
Adolph, K.E., Bertenthal, B.I., Boker, S.M., Goldfield, E.C., & Gibson, E.J. ( 1997). Learning in the development of infant locomotion. Monographs of the Society for Research in Child Development, 62(3).
2.
Bajracharya, M., Howard, A., Matthies, L.H., Tang, B., & Turmon, M. ( 2008). Autonomous off-road navigation with end-to-end learning for the LAGR program. Journal of Field Robotics, 26(1), 3-25.
3.
Blum, A. ( 1997). Selection of relevant features and examples in machine learning. Artificial Intelligence, 97, 245- 271.
4.
Bur, A., Tapus, A., Ouerhani, N., Siegwar, R., & Hiigli, H. ( 2006). Robot navigation by panoramic vision and attention guided features. In Proceedings of the 18th International Conference on Pattern Recognition (pp. 695-698). IEEE.
5.
Chemero, A. ( 2003). An outline of a theory of affordances. Ecological Psychology, 15(2), 181-195.
6.
Chemero, A., Klein, C., & Cordeiro, W. ( 2003). Events as changes in the layout of affordances. Ecological Psychology, 15(1), 19-28.
7.
Collett, T. ( 1977). Stereopsis in toads. Nature, 267, 349-351.
8.
Cornus, S., Montagne, G., & Laurent, M. ( 1999). Perception of a stepping-across affordance. Ecological Psychology, 11(4), 249-267.
9.
Dash, M. & Liu, H. ( 1997). Feature selection for classification. Intelligent Data Analysis, 1, 131-156.
10.
Fitzpatrick, P. & Metta, G. ( 2003). Grounding vision through experimental manipulation. Philosophical Transactions of the Royal Society: Mathematical, Physical, and Engineering Sciences, 361(1811), 2165-2185.
11.
Fitzpatrick, P., Metta, G., Natale, L., Rao, A., & Sandini, G. ( 2003). Learning about objects through action -initial steps towards artificial cognition. In Proceedings of the IEEE International Conference on Robotics and Automation (pp. 3140-3145).
12.
Floreano, D., Kato, T., Marocco, D., & Sauser, E. ( 2004). Coevolution of active vision and feature selection. Biological Cybernetics, 90, 218-228.
13.
Gibson, E. & Walk, R.D. ( 1960). The visual cliff. Scientific American , 202, 64-71.
14.
Gibson, E.J. ( 2000). Perceptual learning in development: Some basic concepts . Ecological Psychology, 12(4), 295- 302.
15.
Gibson, E.J. ( 2003). The world is so full of a number of things: On specification and perceptual learning. Ecological Psychology, 15(4), 283-288.
16.
Gibson, E.J., Riccio, G., Schmuckler, M.A., Stoffregen, T.A., Rosenberg, D., & Taromina, J. ( 1987). Detection of the traversability of surfaces by crawling and walking infants. Journal of Experimental Psychology, 13(4), 533-544.
17.
Gibson, J.J. ( 1986). The ecological approach to visual perception. Mahwah, NJ: Lawrence Erlbaum Associates. (Original work published 1976.)
18.
Griffith, S., Sinapov, J., Miller, M., & Stoytchev, A. ( 2009). Toward interactive learning of object categories by a robot: A case study with container and non-container objects. In Proceedings of the IEEE 8th International Conference on Development and Learning (Shanghai, China).
19.
Ingle, D. & Cook, J. ( 1977). The effects of viewing distance upon size preference of frogs for prey. Vision Research, 17, 1009-1019.
20.
Jackel, L.D., Krotkov, E., Perschbacher, M., Pippine, J., & Sullivan, C. ( 2007). The DARPA LAGR program: Goals, challenges, methodology, and phase I results. Journal of Field Robotics, 23(11-12), 945-973.
21.
Jiang, Y. & Mark, L. ( 1994). The effect of gap depth on the perception of whether a gap is crossable. Perception and Psychophysics, 56(6), 691-700.
22.
Jung, B. & Sukhatme, G. ( 2004). Detecting moving objects using a single camera on a mobile robot in an outdoor environment. In Proceedings of the 8th International Conference on Intelligent Autonomous Systems (pp. 980- 987).
23.
Kim, D., Sun, J., Oh, S.M., Rehg, J.M., & Bobick, A. ( 2006). Traversability classification using unsupervised on-line visual learning for outdoor robot navigation. In Proceedings of the IEEE International Conference on Robotics and Automation . Orlando, FL.
Kira, K. & Rendell, L.A. ( 1992). A practical approach to feature selection. In Proceedings of the 9th International Workshop on Machine Learning (pp. 249-256). San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.
26.
Kononenko, I., Simec, E., & Robnik-Sikonja, M. (1997). Overcoming the myopia of inductive learning algorithms with RELIEFF. Applied Intelligence , 7(1), 39-55.
27.
Kraft, D., Pugeault, N., Baseski, E., Popovic, M., Kragic, D., Kalkan, S., et al. (2008). Birth of the object: Detection of objectness and extraction of object shape through object-action complexes. International Journal of Humanoid Robotics, 5(2).
28.
Li, F. & Kosecka, J. ( 2006). Probabilistic location recognition using reduced feature set. In Proceedings of the IEEE International Conference on Robotics and Automation (pp. 3405-3410).
29.
Lock, A. & Collett, T. ( 1979). A toads devious approach to its prey: A study of some complex uses of depth vision. Journal of Comparative Physiology , 131, 179-189.
30.
Marcilly, R. & Luyat, M. ( 2008). The role of eye height in judgment of an affordance of passage under a barrier. Current Psychology Letters: Behavior, Brain and Cognition, 24(1).
31.
Montesano, L., Lopes, M., Bernardino, A., & Santos-Victor, J. (2008). Learning object affordances: From sensory-motor coordination to imitation. IEEE Transactions on Robotics, 24(1), 15-26.
32.
Moore, A. & Lee, M. ( 1994). Efficient algorithms for minimizing cross validation error. In Proceedings of the 11th International Conference on Machine Learning (pp. 190-198).
33.
Ollis, M., Huang, W.H., Happold, M., & Stancil, B.A. ( 2008). Image-based path planning for outdoor mobile robots. In Proceedings of the IEEE International Conference on Robotics and Automation (pp. 2723-2728). IEEE.
34.
Peng, J. & Peters, A. ( 2005). Extraction of salient features for mobile robot navigation via teleoperation. In Proceedings of the 24th American Control Conference (Vol. 7, pp. 4903-4908).
35.
Petrick, R., Kraft, D., Mourão, K., Pugeault, N., Krüger, N., & Steedman, M. ( 2008). Representation and integration: Combining robot control, high-level planning, and action learning. In Proceedings of the 6th International Cognitive Robotics Workshop (pp. 32-41).
36.
Sahin, E., Çakmak, M., Dogar, M.R., Ugur, E., & Üçoluk, G. (2007). To afford or not to afford: A new formalization of affordances toward affordance-based robot control. Adaptive Behavior, 15(4), 447-472.
37.
Sedgwick, H.A. ( 2001). Visual space perception. In E. B. Goldstein (Ed.), Blackwell handbook of perception (chap. 5). Wiley-Blackwell.
38.
Shneier, M., Chang, T., Hong, T., Shackleford, W., Bostelman, R., & Albus, J.S. ( 2008). Learning traversability models for autonomous mobile vehicles. Autonomous Robots, 24(1), 69-86.
39.
Sinapov, J. & Stoytchev, A. ( 2008). Detecting the functional similarities between tools using a hierarchical representation of outcomes. In Proceedings of the IEEE 7th International Conference on Development and Learning .
40.
Szokolszky, A. ( 2003). An interview with Eleanor Gibson. Ecological Psychology, 15(4), 271-281.
41.
Ugur, E., Dogar, M.R., Soysal, O., Çakmak, M., & Sahin, E. ( 2006). MACSim: Physics-based simulation of the KURT3D robot platform for studying affordances (Tech. Rep.). MACS Project Deliverable.
42.
Ugur, E., Oztop, E., & Sahin, E. ( 2009). Affordance learning from range data for multi-step planning . In Proceedings of the 9th International Conference on Epigenetic Robotics (EpiRob09) (Vol. 146, pp. 177-184). Lund: Lund University Cognitive Studies.
Warren, W.H. ( 1984). Perceiving affordances: Visual guidance of stair climbing . Journal of Experimental Psychology, 105(5), 683-703.
45.
Warren, W.H. & Whang, S. ( 1987). Visual guidance of walking through apertures: body-scaled information for affordances. Journal of Experimental Psychology , 13(3), 371-383.
46.
Wörgötter, F., Agostini, A., Krüger, N., Shylo, N., & Porr, B. ( 2009). Cognitive agents: a procedural perspective relying on the predictability of object-action-complexes (OACs). Robotics and Autonomous Systems, 57(4), 420-432.
47.
Zhang, S., Lihua, X., & Adams, M.D. ( 2005). Entropy based feature selection scheme for real time simultaneous localization and map building. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1175-1180).
