Evidential reasoning for building environment maps

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 the Dempster-Shafer theory for evidential reasoning. This approach provides a mechanism to explicitly model ignorance which is desirable when dealing with an unknown environment. We present results obtained from this approach on a laboratory stereo sequence and contrast these with results obtained from the traditional Bayesian approach