Case studies of applying Gibson's ecological approach to mobile robots

Gibson's ecological approach to perception has recently received significant attention in the robotics literature, The approach relies on the identification and application of affordances for a behaviour. However, determining suitable affordances has been treated as an art rather than a science. This paper presents a methodology for deciding whether an affordance-based approach should be pursued for a specific behaviour and for isolating a reliable affordance. Three case studies on three mobile robots are presented which used this methodology successfully. The case studies illustrate the advantages and limitations of affordances, as well as offer practical insights into applying the ecological approach.

[1]  Marcel Schoppers,et al.  Reactive Combination of Belief Over Time Using Direct Perception , 1997, IJCAI.

[2]  Robin R. Murphy,et al.  Lessons learned in integrating sensing into autonomous mobile robot architectures , 1997, J. Exp. Theor. Artif. Intell..

[3]  Robin R. Murphy.  An artificial intelligence approach to the 1994 AUVS Unmanned Ground Robotics Competition , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[4]  H. Gardner,et al.  The Mind's New Science , 1985 .

[5]  Robin R. Murphy,et al.  Autonomous navigation in a manufacturing environment , 1990, IEEE Trans. Robotics Autom..

[6]  F. C. Volkmann,et al.  3 – Vision in Fishes: Color and Pattern , 1978 .

[7]  Tsai Hong Hong,et al.  Real-time Obstacle Avoidance Using Central Flow Divergence and Peripheral Flow | NIST , 1995 .

[8]  D. Stork.  Generic object recognition using form & function , 1996 .

[9]  Michael J. Swain,et al.  GARGOYLE: An Environment for Real-Time, Context-Sensitive Active Vision , 1996, AAAI/IAAI, Vol. 2.

[10]  Michael P. Wellman,et al.  Planning and Control , 1991 .

[11]  Fausto Giunchiglia,et al.  FUR: Understanding functional reasoning , 1989, Int. J. Intell. Syst..

[12]  Michael J. Swain,et al.  Indexing via color histograms , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[13]  David Marr,et al.  VISION A Computational Investigation into the Human Representation and Processing of Visual Information , 2009 .

[14]  J. Gibson.  The Ecological Approach to Visual Perception , 1979 .

[15]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[16]  Martin Herman,et al.  Real-time obstacle avoidance using central flow divergence and peripheral flow , 2017, Proceedings of IEEE International Conference on Computer Vision.

[17]  Robin R. Murphy.  A Strategy for the Fine Positioning of a Mobile Robot using Texture , 1990, Other Conferences.

[18]  William H. Warren,et al.  Robot navigation from a Gibsonian viewpoint , 1994, Proceedings of IEEE International Conference on Systems, Man and Cybernetics.

[19]  J. Piaget,et al.  The Psychology of the Child , 1969 .

[20]  L. Stark,et al.  Dissertation Abstract , 1994, Journal of Cognitive Education and Psychology.

[21]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[22]  Ian Horswill,et al.  Polly: A Vision-Based Artificial Agent , 1993, AAAI.

[23]  Marie-Christine Jaulent,et al.  Part hierarchies of object shape for recognition , 1994, Other Conferences.

[24]  Yukinori Kakazu,et al.  Explorations of perceptional mechanisms for adaptive agents , 1996, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96.

[25]  D. B. Judd.  Standard Response Functions for Protanopic and Deuteranopic Vision , 1944 .