Vehicular MultiCamera Sensor System for Automated Visual Inspection of Electric Power Distribution Equipment In this paper, we present a multicamera sensor system along with its control algorithm for automated visual inspection from a moving vehicle. To accomplish this task, we propose a unique hardware configuration consisting of a frontal stereo vision system, six lateral cameras motorized to tilt, and a GPSIMU sensor mounted on the roof of a car. From the frontal stereo system, we detect electric poles and estimate their corresponding 3D positions. Based on this 3D estimation, the tilt angles of the motorized lateral cameras are controlled in realtime to capture high resolution images of the equipment  typically installed a few meters above the road surface. In addition, inertial odometry information from the GPSIMU module is utilized for pose estimation, object localization, and reidentification among cameras. Experimental results demonstrate the efficiency and robustness of our system for automated electric equipment maintenance, which can reduce human effort significantly.

Robust and Efficient Vehicles Motion Estimation with LowCost MultiCamera and OdometerGyroscope In this paper, we present a robust and efficient estimation approach with multicamera, odometer and gyroscope. Robust initialization, tightlycoupled optimization estimator and multicamera loopclosure detection are utilized in the proposed approach. In initialization, the measurements of odometer and gyroscope are used to compute scale, and then estimate the bias of sensors. In estimator, the preintegration of odometer and gyroscope is derived and combined with the measurements of multicamera to estimate the motion in a tightlycoupled optimization framework. In loopclosure detection, a connection between different cameras of the vehicle can be built, which significantly improve the success rate of loopclosure detection. The proposed algorithm is validated in multiple realworld datasets collected in different places, time, weather and illumination. Experimental results show that the proposed approach can estimate the motion of vehicles robustly and efficiently.