Department Publications

Device free detection and localization is a promising and a very practical research area where installation of expensive sensors and/or tagging the intruder is not feasible. This paper reports a mesh network developed for device free trespasser detection. We use the Received Signal Strength Indicator (RSSI) measurements of the wireless links within the mesh as the sole sensing mechanism. A fingerprint of RSSI measurements characterizes the environment under normal conditions including multi-path effects. A technique to differentiate RSSI variations due to trespassers from those due to multi-path effects is demonstrated. The results of the experiments conducted in an outdoor environment have verified that the proposed method can be used to detect trespassers successfully. The reliability of the detection is improved by cross-correlating RSSI variations among the multiple links in the mesh. The ability to extend …

Difficult conditions on outdoor terrains make outdoor autonomy for rovers, a challenging task. The conventional wheel odometry method uses orientation measurements to assume a momentary plane to apply wheel encoder readings. On uneven terrains, this method often gives poor results for position tracking, and therefore rarely used. To improve the conventional odometry motion model, immediate terrain data can be used. This paper proposes a novel state variable extension (SVE) method to establish a connection between state space variables of a terrain rover by combining terrain point clouds with rover kinematics. The simulation results show that when the 2D state variables (x, y, yaw) are known, the 2D state can be extended to its 3D state (x, y, z, roll, pitch, yaw) with minimal error. The proposed SVE method is employed in a particle filter to determine the 2D state variables, which in turn results in achieving …