Abstract
A scheme is presented that uses the self-motion of a robot, equipped with a single visual sensor, to navigate in a safe manner. The motion strategy used is modelled on the motion of insects that effectively have a single eye and must move in order to determine range. The essence of the strategy is to employ a zigzag motion in order to (a) estimate the range to objects and (b) know the safe distance of travel in the present direction. An example is presented of a laboratory robot moving in a cluttered environment. The results show that this motion strategy can be successfully employed in an autonomous robot to avoid collisions.
Similar content being viewed by others
References
Anderson CS, Madsen CB, Sorensen JJ, Kirkeby NOS, Jones JP, Christensen HI (1992) Navigation using range images on a mobile robot. Robotics Auton Syst 10:147–160
Anderson TL, Donarth M (1990) Animal behaviour as a paradigm for developing robot autonomy. Robotics Auton Syst 6:145–168
Arkin RC (1990) Integrating behavioral, perceptual and world knowledge in reactive navigation. Robotics Auton Syst 6:105–122
Bastian J, Esch H (1970) The nervous control of the indirect flight muscles of the honey bee. Z Vgl Physiol 67:307–324
Brooks RA (1991) Intelligence without reason. In: 12th Int Joint Conf on Artificial Intelligence, August, pp 569–595
Gibson JJ (1950) The perception of the visual world. Houghton Mifflin, Boston
Heisenberg M, Wolf R (1993) The sensory-motor link in motion-dependent flight control of flies. In: Miles F. A, Wallman J (eds) Visual motion and its role in the stabilisation of gaze. Elsevier Science Publishers, pp 265–283
Hogan N (1985) Impedence control: an approach to manipulation. J Dyn Syst Meas Contrib 107:1–24
Horridge GA (1986) A theory of insect vision: velocity parallax. Proc R Soc Lond [Biol] 229:13–27
Jarvis RA (1983) A perspective on range finding techniques for computer vision. IEEE Trans Pattern Anal Mach Intell 5–2:122–139
Khatib O (1986) Real-time obstacle avoidance for manipulators and mobile robots. Int J Robotics Res 5–1:90–98
Krogh BH (1984) A generalised potential field approach to obstacle avoidance control. In: Int Robotics Res Conf, August
Lee DN, Reddish PE (1981) Plummeting gannets: a paradigm of ecological optics. Nature 293:293–294
Lehrer M (1990) How bees use peripheral eye regions to localise a frontally positioned target. J Comp Physiol [A] 167:173–185
Lehrer M, Srinivasan MV, Zhang SW, Horridge GA (1988) Motion cues provide the bee's visual world with a third dimension. Nature 6162:356–357
Mayer M, Vogtmann K, Bausenwein B, Wolf R, Heisenberg M (1988) Fight control during ‘free yaw turns’ in Drosophila melanogaster. J Comp Physiol [A] 163:389–399
Nakayama K, Loomis JM (1974) Optical velocity patterns, velocitysensitive neurons, and space perception: a hypothesis. Perception 3:63–80
Newman WS, Hogan N (1987) High speed robot control and obstacle avoidance using dynamic potential functions. In: Robotics Automation. Proceedings IEEE International Conference on Robotics and Automation, Piscataway, NJ, pp 14–22
Prescott T, Mayhew J (1992) Adaptive local navigation. In: Blake A, Yuille A (eds) Active vision. MIT Press, Cambridge, Massachusetts, pp 203–215
Rowell CHF (1989) Descending interneurones of the locust reporting deviation from flight course: what is their role in steering? J Exp Biol 146:177–194
Sobey P, Srinivasan MV (1991) Measurement of optical flow using a generalized gradient scheme. J Opt Soc Am 8:1488–1498
Sobey PJ, Sasaki S, Nagle M, Toriu T, Srinivasan MV (1992) A hardware system for computing image velocity in real-time. In: Batchelor BG, Solomon SS, Waltz FM (eds) Machine vision applications, architectures and systems integration. SPIE 1823:334–341
Srinivasan MV (1990) Generalized gradient schemes for the measurement of two-dimensional image motion. Biol Cybern 63:421–431
Srinivasan MV (1992) Distance perception in insects. Curr Dir Psychol Sci 1–1:22–26
Srinivasan MV, Lehrer M, Kirchner WH, Zhang SW (1991) Range perception through apparent image speed in freely flying honeybees. Vis Neurosci 6:519–535
Srinivasan MV, Lehrer M, Zhang SW, Horridge GA (1989) How honeybees measure their distance from objects of unknown size. J Comp Physiol [A] 165:605–613
Suorsa R, Sridhar B (1990) Validation of vision-based obstacle detection algorithms for low-altitude helicopter flight. In: Chun WH, Wolfe WJ (eds) Mobile robots V. SPIE 1388:90–103
Tistarelli M, Sandini G (1993) On the advantages of polar and log-polar mapping for direct estimation of time-to-impact from optical flow. IEEE Trans Patt Anal Mach Intell 15–4:401–410
Uras S, Girosi F, Verri A, Torre V (1988) A computational approach to motion perception. Biol Cybern 60:79–87
Wagner H (1982) Flow-field variables trigger landing in flies. Nature 297:147–148
Wagner H (1986) 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. Philos Trans R Soc Lond [Biol] 312:581–595
Warren WH, Kurtz KJ (1992) The role of central and peripheral vision in perceiving the direction of self-motion. Percept Psychophys 51:443–454
Wolf R, Heisenberg M (1990) Visual control of straight flight in Drosophila melanogaster. J Comp Physiol [A] 167:269–283
Wolf R, Voss A, Hein S, Heisenberg M (1992) Can a fly ride a bicycle? Philos Trans R Soc Lond [Biol] 337:261–269
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Sobey, P.J. Active navigation with a monocular robot. Biol. Cybern. 71, 433–440 (1994). https://doi.org/10.1007/BF00198919
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/BF00198919