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From Fly Vision to Robot Vision: Re-Construction as a Mode of Discovery

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Sensors and Sensing in Biology and Engineering

Abstract

This chapter addresses basic issues on how vision links up with action and guides locomotion in biological and artificial creatures. The thorough knowledge gained over the past five decades on insects’ sensory-motor abilities and the neuronal substrates involved has provided us with a rich source of inspiration for designing tomorrow’s self-guided vehicles and micro-vehicles, which will be able to cope with unforeseen events on the ground, under water, in the air, in space, on other planets, and inside the human body. Insects can teach us some shortcuts to designing agile autonomous robots. At the same time, constructing these ’biorobots’ based on specific biological principles gives us a unique opportunity of checking the soundness and robustness of these principles by bringing them face to face with the real physical world. Here we describe the visually guided terrestrial and aerial robots we have developed on the basis of our biological findings. Their architecture is akin to that of biological systems in spirit, and so is their parallel and analog mode of signal processing. As we learn more about signal processing and sensory-motor integration in nervous systems, we may eventually be able to design even better machines and micromachines than those which Nature has to offer. The millions of insect species constitute a gigantic untapped reservoir of ideas for highly sophisticated sensors, actuators and control systems.

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References

  • Aloimonos Y (1993) Active Perception. Lawrence Erlbaum, Hillsdale, USA

    Google Scholar 

  • Arkin R (1998) Behavior-based Robotics. MIT Press, Cambridge, USA

    Google Scholar 

  • Ayers J, Davis JL, Rudolph A (2002) Neurotechnolgy for Biomimetic Robots. MIT Press, Cambridge, USA

    Google Scholar 

  • Bajcsy R (1985) Active perception versus passive perception. In: Proc. 3rd IEEE Workshop on Computer Vision, pp 55–59

    Google Scholar 

  • Ballard D (1991) Animate vision. Artificial Intelligence 48: 57–86

    Article  Google Scholar 

  • Barlow HB, Frisby JP, Horridge AH, Jeaves M (eds) (1993) Natural and Artificial Low-level Seeing Systems. Clarendon Press, Oxford

    Google Scholar 

  • Blanes C (1986) Appareil visuel ¨¦l¨¦mentaire pour la navigation ¨¤ vue d’un robot mobile autonome. DEA thesis (Neurosciences). Univ. Aix-Marseille

    Google Scholar 

  • Blanes C (1991) Guidage visuel d’un robot mobile autonome d’inspiration bionique. Dr Thesis, National Polytechnic Institute, Grenoble

    Google Scholar 

  • Braitenberg V (1984) Vehicles. MIT Press, Cambridge, USA

    Google Scholar 

  • Brooks RA (1999) Cambrian Intelligence. MIT Press, Cambridge, USA

    Google Scholar 

  • Buchner E (1984) Behavioral analysis of spatial vision in insects, In: Ali M (ed) Photoreception and Vision in Invertebrates. Plenum, New York, pp 561–621

    Chapter  Google Scholar 

  • Burrows M (1996) The Neurobiology of an Insect Brain. Oxford Univ Press, Oxford

    Book  Google Scholar 

  • Chang C, Gaudiano P (2000) Biomimetic Robotics (special issue on). Robotics and Autonomous Systems, 30

    Google Scholar 

  • Cliff D, Husbands P, Meyer JA, Wilson SW (1994) From animals to animats III. In: Proc Intern Conf on Simulation of Adaptive Behavior. MIT Press, Cambridge, USA

    Google Scholar 

  • Collett T, Land M (1975) Visual control of flight behaviour in the hoverfly Syritta Pipiens L. J Comp Physiol A 99: 1–66

    Article  Google Scholar 

  • Collett TS (1978) Peering: a locust behaviour pattern for obtaining motion parallax information. J Exp Biol 76: 237–241

    Google Scholar 

  • Coombs D, Roberts K (1992) Bee-Bot: Using the peripheral optic flow to avoid obstacles. In: Intelligent Robots and Computer Vision XI, SPIE 1835, Bellingham, USA pp 714–725

    Google Scholar 

  • Douglas R, Mahowald M, Mead C (1995) Neuromorphic engineering. Ann Rev Neurosci 18: 255–281

    Article  PubMed  CAS  Google Scholar 

  • Douglass JK, Strausfeld NJ (1996) Visual motion-detecting circuits in flies: parallel direction-and non-direction-selective pathways between the medulla and lobula plate. J Neurosci 16: 4551–4562

    PubMed  CAS  Google Scholar 

  • Duchon AP, Warren WH (1994) Robot navigation from a Gibsonian viewpoint. IEEE Intern Conf On Syst, Man and Cybernetics, San Antonio, USA, IEEE Press, Los Alamitos, USA, pp 2272–2277

    Google Scholar 

  • Franceschini N (1975) Sampling of the visual environment by the compound eye of the fly: fundamentals and applications. In: Snyder A, Menzel R (eds) Photoreceptor Optics, Chap. 17, Springer, Berlin, pp 98–125

    Chapter  Google Scholar 

  • Franceschini N (1984) Chromatic organisation and sexual dimorphism of the fly retinal mosaic. In: Borsellino A, Cervetto L (eds) Photoreceptors, Plenum: New York, pp 319–350

    Google Scholar 

  • Franceschini N (1985) Early processing of colour and motion in a mosaic visual system. Neurosci Res, Suppl 2: 17–49

    Google Scholar 

  • Franceschini N (1996) Engineering applications of small brains. Future Electron Devices Journal, Suppl 7: 38–52

    CAS  Google Scholar 

  • Franceschini N, Chagneux R (1997) Repetitive scanning in the fly compound eye. In: Elsner N, Wässle H (eds) Göttingen Neurobiology Rep, Georg Thieme, Stuttgart, 279

    Google Scholar 

  • Franceschini N, Blanes C, Oufar L (1986) Passive noncontact velocity sensor (in French). Dossier Technique ANVAR/DVAR N¡ã 51, 549, Paris

    Google Scholar 

  • Franceschini N, Pichon JM, Blanes C (1992) From insect vision to robot vision. Phil Trans R Soc Lond B 337: 283–294

    Article  Google Scholar 

  • Franceschini N, Pichon JM, Blanes C (1997) Bionics of visuomotor control. In: Gomi T (ed) Evolutionary Robotics: From Intelligent Robots to Artificial Life. AAAI Books, Ottawa, Canada, pp 49–67

    Google Scholar 

  • Franceschini N, Riehle A, Le Nestour A (1989) Directionally Selective Motion Detection by Insect Neurons. In: Stavenga DG, Hardie RC (eds) Facets of Vision, Berlin, Springer, Chap. 17, pp 360–390

    Google Scholar 

  • Gibson JJ (1958) Visually controlled locomotion and visual orientation in animals. Brit J Psychol 49: 182–194

    Article  PubMed  CAS  Google Scholar 

  • Götz KG (1969) Flight control in Drosophila by visual perception of motion. Kyb 4: 199–208

    Article  Google Scholar 

  • Goulet M, Campan R (1981) The visual perception of the relative distance in the wood cricket Nemobius sylvestris. Physiol Entomol 6: 357–387

    Article  Google Scholar 

  • Hardie RC (1985) Functional organization of the fly retina, In: Ottoson D (ed) Progress in Sensory Physiology 5, Springer, Berlin

    Google Scholar 

  • Harrison R, Koch C (2000) A silicon implementation of the fly’s optomotor control system. Neural Computation 12: 2291–2304

    Article  PubMed  CAS  Google Scholar 

  • Hausen K (1984) The lobula complex of the fly: structure, function and significance in visual behaviour. In: Ali MA (ed), Photoreception and Vision in Invertebrates. Plenum, New York, pp. 523–559

    Chapter  Google Scholar 

  • Hausen K, Egelhaaf M (1989) Neural mechanisms of visual course control in insects. In: Stavenga DG, Hardie RC (eds) Facets of Vision, Springer, Berlin, Chap. 18 pp 391–424

    Chapter  Google Scholar 

  • Horridge GA (1987) The evolution of visual processing and the construction of seeing systems. Proc R Soc Lond B 230: 279–292

    Article  PubMed  CAS  Google Scholar 

  • Hoyle G (1977) Identified Neurons and Behavior of Arthropods. Plenum, New York

    Book  Google Scholar 

  • Huber SA, Bülthoff HH (1997) Modeling obstacle avoidance behavior of flies using an adaptive autonomous agent. Proc 7th Int Conf Artif Neural Networks, ICANN 97, Springer, Berlin, pp 709–714

    Google Scholar 

  • Ichikawa M, Yamada H, Takeuchi J (2001) Flying robot with biologically inspired vision. J Robotics and Mechatronics 6: 621–624

    Google Scholar 

  • Iida F, Lambrinos D (2000) Navigation in an autonomous flying robot by using a biologically inspired visual odometer. In: McKee GT, Schenker PS (eds) SPIE, Vol. 4196, Sensor Fusion and Decentralized Control in Robotic Systems III

    Google Scholar 

  • Indiveri G, Kramer J, Koch C (1996) System implementations of analog VLSI velocity sensors. IEEE Micro 16: 40–49

    Article  Google Scholar 

  • Kirchner WH, Srinivasan MV (1989) Freely flying honeybees use image motion to estimate distance. Naturwissenschaffen 76: 281–282

    Article  Google Scholar 

  • Koenderink JJ (1986) Optic flow. Vis Res 26: 161–180

    Article  PubMed  CAS  Google Scholar 

  • Krapp H, Hengstenberg B, Hengstenberg R (1998) Dendritic structure and receptive-field organisation of optic flow processing inter-neurons in the fly. J Neurophysiol 79: 1902–1917

    PubMed  CAS  Google Scholar 

  • Lambrinos D, Möller R, Labhart T, Pfeifer R, Wehner R (2000) A mobile robot employing insect strategies for navigation. Robotics and Autonomous Systems 30: 39–64

    Article  Google Scholar 

  • Lee DN (1970) The optical flow field: the foundation of vision. Phil Trans R Soc Lond B 290: 169–179

    Article  Google Scholar 

  • Lehrer M Srinivasan MV, Zhang SW, Horridge GA (1988) Motion cues provide the bee’s visual world with a third dimension. Nature 332: 356–357

    Article  Google Scholar 

  • Lewis MA, Arbib M (1999) Biomorphic Robots (Special issue on). Autonomous robots 77

    Google Scholar 

  • Maes P (1991) Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back. MIT Press, Cambridge, USA

    Google Scholar 

  • Martin N, Franceschini N (1994) Obstacle avoidance and speed control in a mobile vehicle equipped with a compound eye. In: Masaki I (ed) Intelligent Vehicles, MIT Press, Cambridge, USA, pp 318–386

    Google Scholar 

  • Mead CA (1989) Analog VLSI and Neural Systems. Addisson-Wesley, Reading

    Book  Google Scholar 

  • Miles FA, Wallman J (1993) Visual Motion and its Role in the Stabilization of Gaze. Elsevier, Amsterdam

    Google Scholar 

  • Möller R (2000) Insect visual homing strategies in a robot with analog processing. Biol Cyb 83: 231–243

    Article  Google Scholar 

  • Mura F, Franceschini N (1994) Visual control of altitude and speed in a flying agent. In: Cliff D, Husbands P, Meyer JA, Wilson SW (eds) From Animals to Animats, MIT Press, Cambridge, USA, pp 91–99

    Google Scholar 

  • Mura F, Franceschini N (1996a) Obstacle avoidance in a terrestrial mobile robot provided with a scanning retina. In: Aoki M, Masaki I (eds) Intelligent Vehicles II, pp 47–52

    Google Scholar 

  • Mura F, Franceschini N (1996b) Biologically inspired ’retinal scanning’ enhances motion perception of a mobile robot. Proc 1st Europe-Asia Congress on Mechatronics, Vol. 3, Bourjault A, Hata S (eds) ENSM, Besançon, pp 934–940

    Google Scholar 

  • Mura F, Shimoyama I (1998) Visual guidance of a small mobile robot using active, biologically-inspired eye movements. In: Proc IEEE Intern Conf Rob Automation 3: 1859–1864

    Google Scholar 

  • Nachtigall W (2002) Bionik, 2nd edn. Springer, Berlin

    Book  Google Scholar 

  • Nakayama K, Loomis JM (1974) Optical velocity patterns, velocity sensitive neurons and space perception: a hypothesis. Perception 3: 63–80

    Article  PubMed  CAS  Google Scholar 

  • Netter T, Franceschini N (1999) Neuromorphic optical flow sensing for nap-of the-earth flight. In: Mobile robots XIV, SPIE Vol. 3838, Bellingham, USA, pp 208–216

    Google Scholar 

  • Netter T, Franceschini N (2002) A robotic aircraft that follows terrain using a neuromorphic eye. In: Intelligent Robots and Systems, Proc IROS2002, EPFL, Lausanne, pp 129–134

    Google Scholar 

  • Neumann TR, Bülthoff HH (2001) Insect inspired visual control of translatory flight. Proc Europ Conference on Artificial Life, ECAL 2001, Springer, Berlin, pp 627–636

    Google Scholar 

  • Pfeiffer R, Scheier C (2001) Understanding Intelligence. MIT Press, Cambridge, USA

    Google Scholar 

  • Pichon JM, Blanes C, Franceschini N (1989) Visual guidance of a mobile robot equipped with a network of self-motion sensors. In: Wolfe WJ, Chun WH (eds) Mobile Robots IV. Proc SPIE I195, Bellingham, USA, pp 44–53

    Google Scholar 

  • Reichardt W (1987) Evaluation of optical motion information by movement detectors J Comp Physiol A 161: 533–547

    Article  PubMed  CAS  Google Scholar 

  • Reichardt W, Poggio T (1976) Visual control of orientation behaviour in the fly, Part I: A quantitative analysis. Q Rev Biophys 9: 311–375

    Article  PubMed  CAS  Google Scholar 

  • Riehle A, Franceschini N (1984) Motion detection in flies: parametric control over ON-OFF pathways Exp Br Res 54: 390–394

    Article  CAS  Google Scholar 

  • Rind FC, Blanchard M, Verschure P (2000) Collision avoidance in a robot using looming detectors from a locust. In: McKee GT, Schenker PS (eds) SPIE Vol. 4196: Sensor Fusion and Decentralized Control in Robotic Systems. Bellingham

    Google Scholar 

  • Ruffier F, Viollet S, Amic S, Franceschini N (2003) Bio-inspired optical flow circuits for the visual guidance of micro-air vehicles. Proc Intern Symp on Circuits and Systems (ISCAS 2003), Bangkok, Thailand (in press)

    Google Scholar 

  • Santos-Victor J, Sandini G, Curotto F, Garibaldi S (1995) Divergent stereo for robot navigation: a step forward to a robot bee. Int J Comp Vision 14: 159

    Article  Google Scholar 

  • Sarpeshkar R, Kramer J, Koch C (1998) Pulse Domain Neuromorphic Circuit for Computing Motion. United States Patent Nb 5,78,648

    Google Scholar 

  • Srinivasan M, Venkatesh S (1997) From living eyes to seeing machines Oxford Univ Press, Oxford

    Google Scholar 

  • Srinivasan MV, Chahl JS, Weber K, Venkatesh S (1999) Robot navigation inspired by principle of insect vision. Robotics and Autonomous Systems 26: 203–216

    Article  Google Scholar 

  • Stavenga DG, Hardie RC (eds) (1989) Facets of Vision. Springer, Berlin

    Book  Google Scholar 

  • Strausfeld NJ (1976) Atlas of an Insect Brain. Springer, Berlin

    Book  Google Scholar 

  • Strausfeld NJ (1989) Beneath the compound eye: neuroanatomical analysis and physiological correlates in the study of insect vision. In: Stavenga DG, Hardie RC (eds) Facets of Vision. Springer, Berlin, Chap. 16: 317–359

    Chapter  Google Scholar 

  • Viollet S, Franceschini N (1999) Visual servo-system based on a biologically-inspired scanning sensor, In: Sensor Fusion and Decentralized Control II, SPIE Vol. 3839, Bellingham, USA, pp 144–155

    Google Scholar 

  • Viollet S, Franceschini N (2001) Superaccurate visual control of an aerial minirobot. In: Rückert U, Sitte J, Witkowski U (eds) Autonomous Minirobots for Research and Edutainment. Heinz Nixdorf Institut, Paderborn, Germany, pp 215–224

    Google Scholar 

  • Vittoz E (1994) Analog VLSI signal processing: why, where and how? J VLSI Signal Proc 8: 27–44

    Article  Google Scholar 

  • Wagner H (1982) Flow-field variables trigger landing in flies. Nature 297: 147–148

    Article  Google Scholar 

  • Wagner H (1986) Flight performance and visual control of flight of the free-flying housefly Musca domestica, I/II/III. Phil Trans R Soc Lond B 312: 527–600

    Article  Google Scholar 

  • Webb B (2001) Can robots make good models of biological behavior? Behav Brain Sci 24: 6

    Google Scholar 

  • Webb B (2002) Robots in invertebrate neuroscience. Nature 417: 359–363

    Article  PubMed  CAS  Google Scholar 

  • Webb B, Consi T (2001) Biorobotics. MIT Press, Cambridge, USA

    Google Scholar 

  • Wehner R (1981) Spatial Vision in Arthropods. In: Autrum HJ (ed) Handbook Sens Physiol, Vol. VII/6C, Springer, Berlin, pp 288–616

    Google Scholar 

  • Whiteside TC, Samuel DG (1970) Blur zone. Nature 225: 94–95

    Article  PubMed  CAS  Google Scholar 

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Authors
  1. Nicolas Franceschini
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Editors and Affiliations

  1. Biocenter, Institute of Zoology — Neurobiology, University of Vienna, Austria

    Friedrich G. Barth

  2. Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, USA

    Joseph A. C. Humphrey

  3. Department of Physiology, University of Arizona, Tucson, AZ, USA

    Timothy W. Secomb

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© 2003 Springer-Verlag Wien

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Franceschini, N. (2003). From Fly Vision to Robot Vision: Re-Construction as a Mode of Discovery. In: Barth, F.G., Humphrey, J.A.C., Secomb, T.W. (eds) Sensors and Sensing in Biology and Engineering. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6025-1_16

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  • DOI: https://doi.org/10.1007/978-3-7091-6025-1_16

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-7091-7287-2

  • Online ISBN: 978-3-7091-6025-1

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