Ecological Robotics

There are striking parallels between ecological psychology and the new trends in robotics and computer vision, particularly regarding how agents interact with the environment. We present some ideas from ecological psychology, including control laws using optic flow, affordances, and action modes, and describe our implementation of these concepts in two mobile robots that can avoid obstacles and chase or flee moving targets solely by using optic flow. The properties of these methods were explored further in simulation. This work ties in with that of others who argue for a methodological approach in robotics that forgoes a central model or planner. Not only might ecological psychology contribute to robotics, but robotic implementations might, in turn, provide a test bed for ecological principles and a source of ideas that could be tested in animals and humans.

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

[2]  R. Bajcsy.  Active perception , 1988 .

[3]  David N. Lee,et al.  A Theory of Visual Control of Braking Based on Information about Time-to-Collision , 1976, Perception.

[4]  H. Evans.  The Study of Instinct , 1952 .

[5]  K. Nakayama,et al.  Optical Velocity Patterns, Velocity-Sensitive Neurons, and Space Perception: A Hypothesis , 1974, Perception.

[6]  M T Turvey,et al.  Optical information about the severity of upcoming contacts. , 1993, Journal of experimental psychology. Human perception and performance.

[7]  Leslie Pack Kaelbling,et al.  Ecological Robotics: Controlling Behavior with Optical Flow , 1995 .

[8]  Ronald C. Arkin,et al.  The impact of cybernetics on the design of a mobile robot system: a case study , 1990, IEEE Trans. Syst. Man Cybern..

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

[10]  Pattie Maes,et al.  Maze Navigation Using Optical Flow , 1996 .

[11]  David N. Lee,et al.  Visual control of locomotion. , 1977, Scandinavian journal of psychology.

[12]  Lisa Meeden.  Towards planning: incremental investigations into adaptive robot control , 1995 .

[13]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[14]  Andrew Duchon.  Maze Navigation Using Optical Flow , 1996 .

[15]  J. Tresilian.  Empirical and theoretical issues in the perception of time to contact. , 1991, Journal of experimental psychology. Human perception and performance.

[16]  Gregor Schöner,et al.  Dynamics of behavior: Theory and applications for autonomous robot architectures , 1995, Robotics Auton. Syst..

[17]  William Rowan,et al.  The Study of Instinct , 1953 .

[18]  Ta Camus,et al.  Real-Time Optical Flow , 1995 .

[19]  M. Srinivasan,et al.  Range perception through apparent image speed in freely flying honeybees , 1991, Visual Neuroscience.

[20]  E. Reed.  The Ecological Approach to Visual Perception , 1989 .

[21]  M. Goodale,et al.  The visual brain in action , 1995 .

[22]  Luc Steels,et al.  Building agents out of autonomous behavior systems , 1995 .

[23]  N. Franceschini,et al.  From insect vision to robot vision , 1992 .

[24]  Hans P. Moravec.  Rover Visual Obstacle Avoidance , 1981, IJCAI.

[25]  J. Gibson.  Visually controlled locomotion and visual orientation in animals. , 1998, British journal of psychology.

[26]  D J Hannon,et al.  Eye movements and optical flow. , 1990, Journal of the Optical Society of America. A, Optics and image science.

[27]  Dana H. Ballard,et al.  Animate Vision , 1991, Artif. Intell..

[28]  William Bechtel,et al.  Multiple levels of inquiry in cognitive science , 1990 .

[29]  R. Hetherington.  The Perception of the Visual World , 1952 .

[30]  Maja J. Mataric,et al.  Integration of representation into goal-driven behavior-based robots , 1992, IEEE Trans. Robotics Autom..

[31]  H. Wagner.  Flight Performance and Visual Control of Flight of the Free-Flying Housefly (Musca Domestica L.) III. Interactions Between Angular Movement Induced by Wide- and Smallfield Stimuli , 1986 .

[32]  Judith A. Effken,et al.  Ecological Perspectives on the New Artificial Intelligence , 1992 .

[33]  William H. Warren,et al.  Visual Control of Posture During Walking: Functional Specificity , 1996 .

[34]  Yiannis Aloimonos,et al.  Is visual reconstruction necessary? obstacle avoidance without passive ranging , 1992, J. Field Robotics.

[35]  Nils J. Nilsson,et al.  Shakey the Robot , 1984 .

[36]  B A Kay,et al.  Visual control of posture during walking: functional specificity. , 1996, Journal of experimental psychology. Human perception and performance.

[37]  Lee Dn,et al.  The optic flow field: the foundation of vision. , 1980 .

[38]  J. Gibson,et al.  Parallax and perspective during aircraft landings. , 1955, The American journal of psychology.

[39]  W. Warren.  Action modes and laws of control for the visual guidance of action , 1988 .

[40]  M. Turvey,et al.  Ecological laws of perceiving and acting: In reply to Fodor and Pylyshyn (1981) , 1981, Cognition.

[41]  Dave Cliff,et al.  The computational hoverfly; a study in computational neuroethology , 1991 .

[42]  J. J. Gibson.  The theory of affordances , 1977 .

[43]  G. Ryle,et al.  心的概念 = The concept of mind , 1962 .

[44]  Svetha Venkatesh,et al.  Insect inspired behaviours for the autonomous control of mobile robots , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[45]  Werner Reichardt,et al.  Processing of optical information by the visual system of the fly , 1986, Vision Research.

[46]  Dana H. Ballard,et al.  Principles of animate vision , 1992, CVGIP Image Underst..

[47]  R. Shaw,et al.  Perceiving, Acting and Knowing : Toward an Ecological Psychology , 1978 .

[48]  James A. Crowell,et al.  The perception of heading during eye movements , 1992, Nature.

[49]  Michael J. Swain,et al.  Task and Environment-Sensitive Tracking, , 1994 .

[50]  Giulio Sandini,et al.  Visual Behaviors for Docking , 1997, Comput. Vis. Image Underst..

[51]  H. Wagner.  Flight performance and visual control of flight of the free-flying housefly (Musca domestica L.) II. Pursuit of targets , 1986 .

[52]  Giulio Sandini,et al.  Robotic bees , 1993, Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93).

[53]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[54]  R A Brooks,et al.  New Approaches to Robotics , 1991, Science.

[55]  Ian Horswill,et al.  Specialization of perceptual processes , 1993 .

[56]  Yiannis Aloimonos,et al.  Obstacle Avoidance Using Flow Field Divergence , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[57]  Paul F. M. J. Verschure,et al.  Designing efficiently navigating non-goal-directed robots , 1993 .

[58]  W H Warren,et al.  Visual control of braking: a test of the tau hypothesis. , 1995, Journal of experimental psychology. Human perception and performance.

[59]  R. A. Brooks,et al.  Intelligence without Representation , 1991, Artif. Intell..

[60]  J. Gibson.  The Senses Considered As Perceptual Systems , 1967 .

[61]  W Reichardt,et al.  Visual control of orientation behaviour in the fly: Part I. A quantitative analysis , 1976, Quarterly Reviews of Biophysics.