Attractor Dynamics to Fuse Strongly Perturbed Sensor Data

  title={Attractor Dynamics to Fuse Strongly Perturbed Sensor Data},
  author={Axel Steinhage and Carsten Winkel and Kay Gorontzi},
We present a new approach to multi sensor fusion which is based on coupled nonlinear attractor dynamics. The state of the dynamics represents the fused estimate of a physical entity measured by multiple sensors. Each sensorreading but also general expert knowledge about the measured system specifies a local stable fixed point (attractor) with a limited basin of attraction of the dynamics. The dynamic state variable converges to a global stable state which is the system’s fused estimate. For the… CONTINUE READING


Publications referenced by this paper.
Showing 1-5 of 5 references

Dynamical Systems for the Behavioral Organization of Autonomous Robot Navigation

A. Steinhage, G. Schöner
Sensor Fusion and Decentralized Control in Robotic Systems: Proc. of SPIE, • 1998
View 1 Excerpt

Multi–Sensor Fusion

R. R. Brooks, S. S. Iyengar
View 1 Excerpt

Special Issue on Data Fusion

P. K. Varshney
Proceedings of the IEEE, • 1997
View 1 Excerpt

Neural Networks for Pattern Recognition

C. M. Bishop
View 1 Excerpt

Microwave remote sensing from space

Proceedings of the IEEE • 1985
View 2 Excerpts

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