Date of Original Version
Abstract or Description
In this paper, we propose a framework for utilizing fixed, ultra-wideband ranging radio nodes to track a moving target node through walls in a cluttered environment. We examine both the case where the locations of the fixed nodes are known as well as the case where they are unknown. For the case when the fixed node locations are known, we derive a Bayesian room-level tracking method that takes advantage of the structural characteristics of the environment to ensure robustness to noise. We also develop a method using mixtures of Gaussians to model the noise characteristics of the radios. For the case of unknown fixed node locations, we present a two-step approach that first reconstructs the target node's path and then uses that path to determine the locations of the fixed nodes. We reconstruct the path by projecting down from a higher-dimensional measurement space to the 2D environment space using non-linear dimensionality reduction with Gaussian Process Latent Variable Models(GPLVMs). We then utilize the reconstructed path to map the locations of the fixed nodes using a Bayesian occupancy grid. We present experimental results verifying our methods in an office environment. Our methods are successful at tracking a moving target node and mapping the locations of fixed nodes using radio ranging data that are both noisy and intermittent.
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) , 1430-1435.