Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Slope Perception from Monoscopic Field Images: Applications to Mobile Robot Navigation

  • Published:
Journal of Intelligent and Robotic Systems Aims and scope Submit manuscript

Abstract

When remotely navigating a mobile robot, operators must estimate the slope of local terrain in order to avoid areas that are too steep to climb or that slope so steeply downward that the operator would lose control of the rover. Although many rovers are equipped with sensor systems to aid the operator in this task, it is sometimes necessary to estimate slopes from two-dimensional images, either when planning operations or when the operator wishes to monitor the results of a sensor system. This experiment compares the operator’s estimates of the slope in Martian terrain with the actual slope determined from three-dimensional data. The ten participants overestimated the slope of the indicated regions by an average of 19° (SD 16°). An analytic model of the error, based on psychophysical analysis, accurately predicts the average magnitude of the errors. Implementation of this model eliminates an average amount of participant error. However, the large estimate variance within and between participants and images still poses a challenge for accurate slope estimation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Burke, J., Murphy, R., Coovert, M., Riddle, D.: Moonlight in Miami: field study of human–robot interaction in the context of an urban search and rescue disaster response training exercise. Hum. Comput. Interact. 19(1), 85–116 (2004)

    Article  Google Scholar 

  2. Casper, J., Murphy, R.: Human–robot interactions during the robot-assisted urban search and rescue response at the World Trade Center. IEEE Trans. Syst. Man Cybern. Part B Cybern. 33(3), 367–385 (2003)

    Article  Google Scholar 

  3. Creem-Regehr, S.H., Gooch, A.A., Sahm, C.S., Thompson, W.B.: Perceiving virtual geographical slant: action influences perception. http://www.psych.utah.edu/∼sc4002/pubs.htm (2003). Accessed 27 January 2004

  4. Drury, J., Scholtz, J., Yanco, H.: Awareness in human–robot interactions. In: IEEE International Conference on Systems, Man and Cybernetics (2003)

  5. Epstein, W., Park, J.: Gibson’s psychophysical hypothesis. Psychol. Bull. 62(3), 180–196 (1964)

    Article  Google Scholar 

  6. Gibson, J.J.: The perception of visual surfaces. Am. J. Psychol. 63, 367–384 (1950)

    Article  Google Scholar 

  7. Kanduri, A.K., Thomas, G., Cabrol, N., Grin, E., Anderson, R.C.: The (in)accuracy of novice rover operators’ perception of obstacle height from monoscopic images. IEEE Trans. Syst. Man Cybern. Part A 35(4), 505–512 (2005)

    Article  Google Scholar 

  8. Lewis, M., Wang, J., Hughes, S., Liu X.: Experiments with attitude: attitude displays for teleoperation. In: IEEE International Conference on Systems, Man and Cybernetics (2003)

  9. NASA: Planetary Data System Database, Mars Pathfinder IMP imager, Presidential Panorama. http://stardev.jpl.nasa.gov/pds/index.jsp (2003). Accessed 11 November 2003

  10. Perrone, J.A.: Slant underestimation: a model based on the size of the viewing aperture. Perception 9, 285–302 (1980)

    Article  Google Scholar 

  11. Perrone, J.A.: Visual slant underestimation: a general model. Perception 11, 641–654 (1982)

    Article  Google Scholar 

  12. Perrone, J.A., Wenderoth, P.M.: Visual slant underestimation. In: Ellis, S.R. (ed.) Pictorial Communication in Virtual and Real Environments, pp. 496–503. Taylor & Francis, London (1981)

    Google Scholar 

  13. Proffitt, D.R., Bhalla, M., Gossweiler, R., Midgett, J.: Perceiving geographical slant. Psychon. Bull. Rev. 2(4), 409–428 (1995)

    Google Scholar 

  14. Proffitt, D.R., Creem, S.H., Zosh, W.D.: Seeing mountains in mole hills: geographical-slant perception. Psychol. Sci. 12(5), 418–423 (2001)

    Article  Google Scholar 

  15. Sheridan, T.: Telerobotics, Automation, and Human Supervisory Control. MIT Press, Cambridge (1992)

    Google Scholar 

  16. Smith, A.H.: Outline convergence versus closure in the perception of slant. Percept. Mot. Skills 9, 259–266 (1959)

    Article  Google Scholar 

  17. Steinfeld, A.: Interface lessons for fully and semi-autonomous mobile robots. IEEE Int. Conf. Robot. Autom. 3, 2752–2757 (2004)

    Google Scholar 

  18. van Erp, J.: Trade-offs between spatial and temporal resolution in driving unmanned ground vehicles. In: Proceedings of the Human Factors and Ergonomics Society 42nd Annual Meeting, pp. 1550–1554 (1998)

  19. Woods, D.D., Tittle, J., Feil, M., Roesler, A.: Envisioning human–robot coordination in future operations. IEEE Trans. Syst. Man Cybern. Part C 34(2), 210–218 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kristopher M. Thornburg.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Xiang, Z., Thomas, G.W., Thornburg, K.M. et al. Slope Perception from Monoscopic Field Images: Applications to Mobile Robot Navigation. J Intell Robot Syst 54, 595–612 (2009). https://doi.org/10.1007/s10846-008-9281-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-008-9281-y

Keywords

Navigation