Abstract
The main contribution of this paper is to present a sensor fusion approach to scene environment mapping as part of a Sensor Data Fusion (SDF) architecture. This approach involves combined sonar array with stereo vision readings. Sonar readings are interpreted using probability density functions to the occupied and empty regions. Scale Invariant Feature Transform (SIFT) feature descriptors are interpreted using gaussian probabilistic error models. The use of occupancy grids is proposed for representing the sensor readings. The Bayesian estimation approach is applied to update the sonar array and the SIFT descriptors' uncertainty grids. The sensor fusion yields a significant reduction in the uncertainty of the occupancy grid compared to the individual sensor readings.
| Original language | English |
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| Title of host publication | Proceedings of the IEEE Systems, Man and Cybernetics Society |
| Number of pages | 6 |
| Publisher | Electrical Engineering/Electronics, Computer, Communications and Information Technology Association |
| Publication date | 2006 |
| Pages | 20-25 |
| Publication status | Published - 2006 |
| Event | Conference on Advances in Cybernetics Systems - Shefield, United Kingdom Duration: 7 Sept 2006 → 8 Sept 2006 Conference number: 5 |
Conference
| Conference | Conference on Advances in Cybernetics Systems |
|---|---|
| Number | 5 |
| Country/Territory | United Kingdom |
| City | Shefield |
| Period | 07/09/2006 → 08/09/2006 |