Visual Estimation of Object Density Distribution through Observation of its Impulse Response

Artashes Mkhitaryan, Darius Burschka

2013

Abstract

In this paper we introduce a novel vision based approach for estimating physical properties of an object such as its center of mass and mass distribution. Passive observation only allows to approximate the center of mass with the centroid of the object. This special case is only true for objects that consist of one material and have unified mass distribution. We introduce an active interaction technique with the object derived from the analogon to system identification with impulse functions. We treat the object as a black box and estimate its internal structure by analyzing the response of the object to external impulses. The impulses are realized by striking the object at points computed based on its external geometry. We determine the center of mass from the profile of the observed angular motion of the object that is captured by a high frame-rate camera. We use the motion profiles from multiple strikes to compute the mass distribution. Knowledge of these properties of the object leads to more energy efficient and stable object manipulation. As we show in our real world experiments, our approach is able to estimate the intrinsic layered density structure of an object.

References

  1. Domokos, G. and Vrkonyi, P. L. (2008 January 7). Geometry and self-righting of turtles. Proc Biol Sci, 275(1630):11-17.
  2. Femmam, S., MSirdi, N. K., and Ouahabi, A. (OCTOBER 2001). Perception and characterization of materials using signal processing techniques. In IEEE Transactions on Instrumentation and Measurement, Vol. 50, No. 5.
  3. Frank, B., Schmedding, R., Stachniss, C., Teschner, M., and Burgard, W. (2010). Learning deformable object models for mobile robot navigation. In Science and Systems Conference (RSS).
  4. Kragic, D., Miller, A. T., and Allen, P. K. (2001). Realtime tracking meets online grasp planning. In IEEE International Conference on Robotics & Automation.
  5. Krotkov, E. (1995). Robotic perception of material. In Proceedings of the International Joint Conference Artifical Intelligence.
  6. Krotkov, E., Klatzky, R., and Zumel, N. (1995). Robotic perception of material: Experiments with shapeinvariant acoustic measures of material type. In Preprints of the fourth international symposium on experimental robotics, iser (not sure).
  7. Kunze, L., Dolha, M. E., Guzman, E., and Beetz, M. (2011). Simulation-based temporal projection of everyday robot object manipulation. In Proc. of the 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2011).
  8. Miller, A. T. and Allen, P. K. (1999). Examples of 3d grasp quality computations. In IEEE International Conference on Robotics & Automation.
  9. T.Tanaka, H., Kushihama, K., Ueda, N., and ichi Hirai, S. (2003). A vision-based haptic exploration. In International Conference on Robotics & Automation.
  10. Yu, Y., Fukuda, K., and Tsujio, S. (1999). Estimation of mass and center of mass of graspless and shape-unknown object. In InternationalConference on Robotics & Automation.
Download


Paper Citation


in Harvard Style

Mkhitaryan A. and Burschka D. (2013). Visual Estimation of Object Density Distribution through Observation of its Impulse Response . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 586-595. DOI: 10.5220/0004199705860595


in Bibtex Style

@conference{visapp13,
author={Artashes Mkhitaryan and Darius Burschka},
title={Visual Estimation of Object Density Distribution through Observation of its Impulse Response},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={586-595},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004199705860595},
isbn={978-989-8565-47-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Visual Estimation of Object Density Distribution through Observation of its Impulse Response
SN - 978-989-8565-47-1
AU - Mkhitaryan A.
AU - Burschka D.
PY - 2013
SP - 586
EP - 595
DO - 10.5220/0004199705860595