Skip to main content
SpringerLink
Log in

A leg proprioception based 6 DOF odometry for statically stable walking robots

  • Published:
Autonomous Robots Aims and scope Submit manuscript

Abstract

This article presents a 3D odometry algorithm for statically stable walking robots that only uses proprioceptive data delivered by joint angle and joint torque sensors embedded within the legs. The algorithm intrinsically handles each kind of emerging statically stable gait and is independent of predefined gait patterns. Additionally, the algorithm can be equally applied to stiff robots as well as to robots with compliant joints. Based on the proprioceptive information a 6 degrees of freedom (DOF) pose estimate is calculated in three steps. First, point clouds, represented by the foot positions with respect to the body frame at two consecutive time steps, are matched and provide a 6 DOF estimate for the relative body motion. The obtained relative motion estimates are summed up over time giving a 6 DOF pose estimate with respect to the start frame. Second, joint torque measurement based pitch and roll angle estimates are determined. Finally in a third step, these estimates are used to stabilize the orientation angles calculated in the first step by data fusion employing an error state Kalman filter. The algorithm is implemented and tested on the DLR Crawler, an actively compliant six-legged walking robot. For this specific robot, experimental data is provided and the performance is evaluated in flat terrain and on gravel, at different joint stiffness settings and for various emerging gaits. Based on this data, problems associated with the odometry of statically stable walking robots are identified and discussed. Further, some results for crossing slopes and edges in a complete 3D scenario are presented.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Boaventura, T., Semini, C., Buchli, J., Frigerio, M., Focchi, M., & Caldwell, D. G. (2012). Dynamic torque control of a hydraulic quadruped robot. In Proceedings of the 2012 IEEE conference on robotics and automation. Saint Paul, USA.

  • Butterfass, J., Grebenstein, M., Liu, H., & Hirzinger, G. (2001). DLR-Hand II: Next generation of a dextrous robot hand. In Proceedings of the 2001 IEEE conference on robotics and automation (pp. 109–114). Seoul, Korea.

  • Chilian, A., Hirschmüller, H., & Görner, M. (2011). Multisensor data fusion for robust pose estimation of a six-legged walking robot. Proceedings of the 2011 IEEE/RSJ international conference on intelligent robots and systems (pp. 2497–2504). San Francisco, CA, USA.

  • Cruse, H. (1990). What mechanisms coordinate leg movement in walking arthropods. Trends in Neuroscience, 13, 15–21.

    Google Scholar 

  • Gassmann, B., Zöllner, J. M., & Dillmann, R. (2004). Navigation of walking robots: Localisation by odometry. Proceedings of the 7th international conference on climbing and walking robots (pp. 953–960). Madrid, Spain.

  • Gassmann, B., Zacharias, F., Zöllner, J. M., & Dillmann, R. (2005). Localization of walking robots. Proceedings of the 2005 international conference on robotics and automation (pp. 1483–1488). Barcelona, Spain.

  • Görner, M., Wimböck, Th, Baumann, A., Fuchs, M., Bahls, T., Grebenstein, M., et al. (2008). The DLR-Crawler, A testbed for actively compliant walking based on the fingers of DLR-Hand II. In Proceedings of the 2008 IEEE/RSJ international conference on intelligent robots and systems (pp. 1525–1531). Nice, France.

  • Görner, M., Wimböck, Th, & Hirzinger, G. (2009). The DLR Crawler: Evaluation of gaits and control of an actively compliant six-legged walking robot. Industrial Robot: An International Journal, 36(4), 344–351.

    Article  Google Scholar 

  • Haralick, R. M., Joo, H., Lee, C.-N., Zhuang, X., Vaidya, V. G., & Kim, M. B. (1989). Pose estimation from corresponding point data. IEEE Transactions on Systems, Man and Cybernetics, 19(6), 1426–1446.

    Article  Google Scholar 

  • Lamon, P., & Siegwart, R. (2004). Inertial and 3D-odometry fusion in rough terrain—Towards real 3D navigation. Proceedings of the 2004 IEEE/RSJ international conference on intelligent robots and systems (pp. 1716–1721). Sendai, Japan.

  • Lin, P.-C., Komsuoglu, H., & Koditschek, D. E. (2005). A leg configuration measurement system for full-body pose estimates in a hexapod robot. IEEE Transactions on Robotics, 21(3), 411–422.

    Article  Google Scholar 

  • Lin, P.-C., Komsuoglu, H., & Koditschek, D. E. (2006). Sensor data fusion for body state estimation in a hexapod robot with dynamical gaits. IEEE Transactions on Robotics, 22(5), 932–943.

    Article  Google Scholar 

  • Ma, J., Susca, S., Bajracharya, M., Matthies, L., Malchano, M., & Wooden, D. (2012). Robust multi-sensor, day/night 6-DOF pose estimation for a dynamic legged vehicle in GPS-denied environments. Proceedings of the 2012 IEEE conference on robotics and automation (pp. 619–626). Saint Paul, USA.

  • Ott, Ch., Roa, M. A., & Hirzinger, G. (2011). Posture and balance control for biped robots based on contact force optimization. Proceedings of the 2011 IEEE-RAS international conference on humanoid robots (pp. 26–33). Bled, Slovenia.

  • Reinstein, M., & Hoffmann, M. (2011). Dead reckoning in a dynamic quadruped robot: Inertial navigation system aided by a legged odometer. Proceedings of the 2011 IEEE conference on robotics and automation (pp. 617–624). Shanghai, China.

  • Roston, G. P., & Krotkov, E. P. (1992). Dead reckoning navigation for walking robots. Proceedings of the 1992 IEEE/RSJ international conference on intelligent robots and systems (pp. 607–612). Raleigh, USA.

  • Stelzer, A., Hirschmüller, H., & Görner, M. (2012). Stereo vision based navigation of a six-legged walking robot in unknown rough terrain. The International Journal of Robotics Research—Special Issue on Robot Vision, 31(4), 381–402.

    Article  Google Scholar 

  • Welch, G., & Bishop, G. (2006). An introduction to the Kalman Filter, Technical Report—TR 95-041, Department of Computer Science. University of North Carolina, Chapel Hill, USA.

Download references

Acknowledgments

We are very thankful to Heiko Hirschmüller for providing us with valuable computer vision literature and fruitful discussions. Further, we want to thank the reviewers for their detailed and constructive comments.

Author information

Authors and Affiliations

  1. Robotics and Mechatronics Center, German Aerospace Center (DLR e.V.), Münchner Str. 20, 82234 , Wessling, Germany

    Martin Görner & Annett Stelzer

Authors
  1. Martin Görner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Annett Stelzer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Martin Görner.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Görner, M., Stelzer, A. A leg proprioception based 6 DOF odometry for statically stable walking robots. Auton Robot 34, 311–326 (2013). https://doi.org/10.1007/s10514-013-9326-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10514-013-9326-3

Keywords

Search

Navigation