Multisensor Filtration and Fusion on a Three-Layer Architecture

Abstract

Using a proposed Three-Layer Architecture, several filtration and fusion techniques are experimented using various sensors. Different scenarios were tested to validate the architecture on three different platforms; a Mobile Robot, a Four-Wheel Vehicle and a Quadcopter. The techniques investigated which yielded the best results were fusing an Infrared sensor along with an Ultrasonic sensor on a Mobile Robot through a Particle Filter and Fuzzy Logic to optimize the fusion. For the Quadcopter, an IMU was fused using Extended Kalman Filter with Fuzzy Logic to compensate for the IMU’s drift. As for the Four-Wheel Vehicle, an IMU with an Encoder was fused to estimate the odometry of the vehicle using an Extended Kalman Filter. Communication between the platforms and the signals was done on a three-layer communication system that uses multimaster package of ROS, I2C and WiFi to communicate between the platforms and the signals being sent and received.