Hostname: page-component-8448b6f56d-tj2md Total loading time: 0 Render date: 2024-04-24T02:53:27.369Z Has data issue: false hasContentIssue false
  • English
  • Français

Robot navigation: implications from search strategies in exploring crayfish

Published online by Cambridge University Press:  26 May 2009

Edith Heußlein ,
Blair W. Patullo  and
David L. Macmillan
Edith Heußlein
Affiliation:
Department of Zoology, University of Melbourne, Victoria 3010, Australia Hochschule Bremen, Fachbereich 7, Fachrichtung Bionik, Internationaler Studiengang Bionik, Neustadtswall 30, D-28199 Bremen, Germany
Blair W. Patullo*
Affiliation:
Department of Zoology, University of Melbourne, Victoria 3010, Australia
David L. Macmillan
Affiliation:
Department of Zoology, University of Melbourne, Victoria 3010, Australia
*
*Corresponding author. Email: b.patullo@zoology.unimelb.edu.au
Get access Rights & Permissions [Opens in a new window]

Summary

Biomimetic applications play an important role in informing the field of robotics. One aspect is navigation – a skill automobile robots require to perform useful tasks. A sub-area of this is search strategies, e.g. for search and rescue, demining, exploring surfaces of other planets or as a default strategy when other navigation mechanisms fail. Despite that, only a few approaches have been made to transfer biological knowledge of search mechanisms on surfaces along the ground into biomimetic applications. To provide insight for robot navigation strategies, this study describes the paths a crayfish used to explore terrain. We tracked movement when different sets of sensory input were available. We then tested this algorithm with a computer model crayfish and concluded that the movement of C. destructor has a specialised walking strategy that could provide a suitable baseline algorithm for autonomous mobile robots during navigation.

Keywords

Terrain classificationSearch pathAutonomous robotsNavigationAlgorithmsLocomotion
Type
Article
Information
Robotica , Volume 28 , Issue 3 , May 2010 , pp. 465 - 475
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Quinn, R. D. and Ritzmann, R. E., “Construction of a hexapod robot with cockroach kinematics benefits both robotics and biology,” Connect. Sci. 10, 239–254 (1998).Google Scholar
2.Ritzmann, R. E., Quinn, R. D., Watson, J. T. and Zill, S. N., “Insect walking and biorobotics: A relationship with mutual benefits,” Bioscience 50, 23 (2000).CrossRefGoogle Scholar
3.Ma, S. G., Tadokoro, N. and Inoue, K., “Influence of the gradient of a slope on optimal locomotion curves of a snake-like robot,” Adv. Robot. 20, 413–428 (2006).CrossRefGoogle Scholar
4.Menciassi, A., Accoto, D. and Gorini, S., “Development of a biomimetic miniature robotic crawler,” Auton. Robot. 21, 155–163 (2006).Google Scholar
5.Klaassen, B., Linnemann, R., Spenneberg, D. and Kirchner, F., “Biomimetic walking robot SCORPION: Control and modelling,” Robot. Auton. Syst. 41, 69–76 (2002).CrossRefGoogle Scholar
6.Deng, X., Schenato, L., Wu, W. C. and Sastry, S. S., “Flapping flight for biomimetic robotic insects: Part I – System modelling,” IEEE Trans. Robotic. Autom. 22 (4), 776–788 (2006).CrossRefGoogle Scholar
7.Franceschini, N., Pichon, J. M., Blanes, C. and Brady, J. M., “From insect vision to robot vision,” Phil. Trans. R. Soc. B 337, 283–294 (1992).Google Scholar
8.Huber, S. A., Franz, M. O. and Bülthoff, H. H., “On robots and flies: Modelling the visual orientation behavior of flies,” Robot. Auton. Syst. 29, 227–242 (1999).CrossRefGoogle Scholar
9.Srinivasan, M. V., Chahl, J. S., Weber, K., Venkatesh, S., Nagle, M. G. and Zhang, S. W., “Robot navigation inspired by principles of insect vision,” Robot. Auton. Syst. 26, 203–216 (1999).CrossRefGoogle Scholar
10.Li, W., Farrell, J. A., Pang, S. and Arrieta, R. M., “Moth-inspired chemical plume tracing on an autonomous underwater vehicle,” IEEE Trans. Robot. 22, 292–307 (2006).Google Scholar
11.Kaliyamoorthy, S., Quinn, R. D. and Zill, S. N., “Force sensors in hexapod locomotion,” Int. J. Robot. Res. 24, 563–574 (2005).CrossRefGoogle Scholar
12.Chapman, T. P. and Webb, B., “A model of antennal wall-following and escape in the cockroach,” J. Comp. Physiol. A 192, 949–969 (2006).Google Scholar
13.Rosano, H. and Webb, B., “A dynamic model of thoracic differentiation for the control of turning in the stick insect,” Biol. Cybern. 97, 229–246 (2007).Google Scholar
14.Webb, B., “Using robots to model animals: A cricket test,” Robot. Auton. Syst. 16, 117–134 (1995).Google Scholar
15.Franz, M. O. and Mallot, H. A., “Biomimetic robot navigation,” Robot. Auton. Syst. 30, 133–153 (2000).Google Scholar
16.Ayers, J., “Underwater walking,” Arthr. Struct. Dev. 33, 347–360 (2004).CrossRefGoogle ScholarPubMed
17.Grasso, F., Consi, T., Mountain, D. and Atema, J., “Biomimetic robot lobster performs chemo-orientation in turbulence using a pair of spatially separated sensors: Progress and challenges,” Robot. Auton. Syst. 30, 115–131 (2000).Google Scholar
18.Lazkano, E., Sierra, B., Astigarraga, A. and Martinez-Otzeta, J. M., “On the use of Bayesian Networks to develop behaviors for mobile robots,” Robot. Auton. Syst. 55, 253–265 (2007).Google Scholar
19.Sarıel, S. and Akın, H. L., “A novel search strategy for autonomous search and rescue robots,” RoboCup 2004: Robot soccer World Cup VIII 3276, 459–466 (2005).Google Scholar
20.Gelenbe, E., Schmajuk, N., Staddon, J. and Reif, J., “Autonomous search by robots and animals: A survey,” Robot. Auton. Syst. 22, 23–34 (1997).Google Scholar
21.Ayers, J., Witting, J., Wilbur, C., Zavracky, P., McGruer, N. and Massa, D., “Biomimetic Robots for Shallow Water Mine Countermeasures,” Proceedings of the autonomous vehicles in mine countermeasures symposium, Naval Postgraduate School (2000).Google Scholar
22.Taubes, G., “Biologists and engineers create a new generation of robots that imitate life,” Science 288, 80–83 (2000).CrossRefGoogle ScholarPubMed
23.Martinez, D., Rochel, O. and Hugues, E., “A biomimetic robot for tracking specific odors in turbulent plumes,” Auton. Robot. 20, 185–195 (2006).Google Scholar
24.Bengtsson, G., Nilsson, E., Rydén, T. and Wiktorsson, M., “Irregular walks and loops combines in small-scale movement of a soil insect: Implications for dispersal biology,” J. Theor. Biol. 231, 299–306 (2004).Google Scholar
25.Bowne, D. R. and White, H. R., “Searching strategy of the painted turtle Chrysemys picta across spatial scales,” Anim. Behav. 68, 1401–1409 (2004).CrossRefGoogle Scholar
26.Wehner, R. and Srinivasan, M. V., “Searching behavior of desert ants, Genus Cataglyphis (Formicidae, Hymenoptera),” J. Comp. Physiol. 142, 315–338 (1981).Google Scholar
27.Şafak, K. K. and Adams, G. G., “Dynamic modelling and hydrodynamic performance of biomimetic underwater robot locomotion,” Auton. Robot. 13, 223–240 (2002).CrossRefGoogle Scholar
28.Chang, C., Chiang, C.-F., Liu, C.-H. and Liu, C.-H., “A lobster-sniffing-inspired method for micro-objects manipulation using electrostatic micro-actuators,” J. Micromech. Microeng. 15, 812–821 (2005).Google Scholar
29.Horner, A. J., Weissburg, M. J. and Derby, C. D., “Dual antennular chemosensory pathways can mediate orientation by Caribbean spiny lobsters in naturalistic flow conditions,” J. Exp. Biol. 207, 3785–3796 (2004).Google Scholar
30.Browne, K. A., Tamburri, M. N. and Zimmer-Faust, R. K., “Modelling quantitative structure-activity relationships between animal behaviour and environmental signal molecules,” J. Exp. Biol. 201, 245–258 (1998).Google Scholar
31.Guenther, C. M., Miller, H. A., Basil, J. A. and Atema, J., “Orientation behaviour of the lobster: Responses to directional chemical and hydrodynamic stimulation of the antennules,” Biol. Bull. 191, 310–311 (1996).Google Scholar
32.Basil, J. A. and Atema, J., “Lobster orientation in turbulent odor plumes: Simultaneous measurement of tracking behaviour and temporal odor patterns,” Biol. Bull. 187, 272–273 (1994).Google Scholar
33.Grasso, F. W. and Basil, J. A., “How lobsters, crayfishes, and crabs locate sources of odor: Current perspectives and future directions,” Curr. Opin. Neurobiol. 12, 721–727 (2002).Google Scholar
34.Weissburg, M. J., Ferner, M. C., Pisut, D. P. and Smee, D. L., “Ecological consequencecs of chemically mediated prey detection,” J. Chem. Ecol. 28, 1953–1970 (2002).Google Scholar
35.Atema, J., “Eddy chemotaxis and odor landscapes: Exploration of nature with animal sensors,” Biol. Bull. 191, 129–138 (1996).Google Scholar
36.Grasso, F. W., Dale, J. H., Consi, T. R., Mountain, D. C. and Atema, J., “Behavior of purely chemotactic robot lobster reveals different odor dispersal patterns in the jet region and the patch field of a turbulent plume,” Biol. Bull. 191, 312–313 (1996).Google Scholar
37.Macmillan, D. L. and Patullo, B. W., “Insights for robotic design from studies of the control of abdominal position in crayfish,” Biol. Bull. 200, 201–205 (2001).Google Scholar
38.Breithaupt, T., “Fan organs of crayfish enhance chemical information flow,” Biol. Bull. 200, 150–154 (2001).CrossRefGoogle ScholarPubMed
39.Patullo, B. W. and Macmillan, D. L., “Corners and bubble wrap: the structure and texture of surfaces influence crayfish exploratory behavior,” J. Exp. Biol. 209, 567–575 (2006).Google Scholar
40.Basil, J. and Sandeman, D., “Crayfish (Cherax destructor) use tactile cues to detect and learn topographical changes in their environment,” Ethology 106, 247–259 (2000).Google Scholar
41.Koch, L. M., Patullo, B. W. and Macmillan, D. L., “Exploring with damaged antennae: Do crayfish compensate for injuries?,” J. Exp. Biol. 209, 3226–3233 (2006).Google Scholar
42.McMahon, A., Patullo, B. W. and Macmillan, D. L., “Exploration in a T-Maze by the crayfish Cherax destructor suggests bilateral comparison of antennal tactile information,” Biol. Bull. 208, 183–188 (2005).Google Scholar
43.Martinez, M. M., Full, R. J. and Koehl, M. A., “Underwater punting by an intertidal crab: A novel gait revealed by the kinematics of pedestrian locomotion in the air versus water,” J. Exp. Biol. 201, 2609–2623 (1998).Google Scholar
44.Wine, J. J. and Krasne, F. B., “The organization of escape behavior in the crayfish,” J. Exp. Biol. 56, 1–18 (1972).CrossRefGoogle ScholarPubMed
45.Bell, W. J., Searching Behavior: The Behavioral Ecology of Finding Resources (Chapman and Hall, London, 1991).Google Scholar
46.Kesel, A. B., Junge, M. M. and Nachtigall, W., Einführung in die angewandte Statistik für Biowissenschaftler (Birkhäuser Verlag, Berlin, 1999).Google Scholar
47.Wallace, D. G., Hamilton, D. A. and Whishaw, I. Q., “Movement characteristics support a role for dead reckoning in organizing exploratory behavior,” Anim. Cogn. 9, 219–228 (2006).Google Scholar
48.Bruski, C. A. and Dunham, D. W., “The importance of vision in agonistic communication of the crayfish Orconectes rusticus. I: An analysis of bout dynamics,” Behavior 103, 83–107 (1987).Google Scholar
49.Delgado-Morales, G., Hernandez-Falcon, J. and Ramon F, F., “Agonistic behavior in crayfish: The importance of sensory inputs,” Crustaceana 77, 1–24 (2004).Google Scholar
50.Van der Velden, J., Zheng, Y., Patullo, B. W. and Macmillan, D. L., “Crayfish can recognize the face of fight opponents,” PLoS ONE 3 (2), e1695 (2008).Google Scholar
51.Cain, M. L., “The analysis of angular data in ecological field studies,” Ecology 70, 1540–1543 (1989).Google Scholar
52.Mardia, K. V., Statistics of Directional Data (Academic Press, London, 1972).Google Scholar
53.Fisher, N. I., Statistical Analysis of Circular Data (Cambridge University Press, Cambridge, 1993).Google Scholar
54.Nolet, B. A. and Mooij, W. M., “Search paths of swans foraging on spatially autocorrelated tubers,” J. Anim. Ecol. 71, 451–462 (2002).Google Scholar
55.Conradt, L., Bodsworth, E. J., Roper, T. J. and Thomas, C. D., “Non-random dispersal in the butterfly Maniola jurtina: Implications for metapopulation models,” Proc. R. Soc. B 267, 1505–1510 (2000).Google Scholar
56.Turchin, P., Quantitative Analysis of Movement: Measuring and Modelling Population Redistribution in Animals and Plants (Sinaur Associates, Sunderland, UK, 1998).Google Scholar
57.Weimerskirch, H., Guionnet, T., Martin, J., Shaffer, S. A. and Costa, D. P, “Fast and fuel efficient? Optimal use of wind by flying albatrosses,” Proc. R. Soc. B 267, 1869–1874 (2000).Google Scholar
58.Cameron, G. N., Spencer, S. R., Eshelman, B. D., Williams, L. R. and Gregory, M. J., “Activity and burrow structure of attwater's pocket gopher (Geomys attwateri),” J. Mammal. 69, 667–677 (1988).Google Scholar
59.Webb, B., “What does robotics offer animal behaviour?,” Anim. Behav. 60, 545–558 (2000)Google Scholar