Robust self-calibration and evidential reasoning for building environment maps

Arun P. Tirumalai; Brian G. Schunck; Ramesh C. Jain

doi:10.1117/12.25270

1 April 1991 Robust self-calibration and evidential reasoning for building environment maps

Arun P. Tirumalai, Brian G. Schunck, Ramesh C. Jain

Proceedings Volume 1383, Sensor Fusion III: 3D Perception and Recognition; (1991) https://doi.org/10.1117/12.25270
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States

Abstract

We address the problem of building a map of the environment utilizing sensory depth information obtained from multiple viewpoints. The desired representation of the environment is in the form of a finite-resolution three-dimensional grid of voxels. Each voxel within the grid is assigned a binary value corresponding to its occupancy state. We present an approach for multi-sensory depth information assimilation based on Dempster-Shafer theory for evidential reasoning. This approach provides a mechanism to explicitly model ignorance which is desirable when dealing with an unknown environment. A fundamental requirement for such an approach to be used is accurate knowledge of the camera motion between two viewpoints. We present a robust least median of squares (LMS) based algorithm to recover this motion which provides a self-calibration mechanism. We present results obtained from this approach on a laboratory stereo sequence.

Citation Download Citation

Arun P. Tirumalai, Brian G. Schunck, and Ramesh C. Jain "Robust self-calibration and evidential reasoning for building environment maps", Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); https://doi.org/10.1117/12.25270

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