Drone SLAM using TDOA-RSS signal with applied EKF on PF data

Abstract

This paper describes the integration of Particle filter data earlier recorded in simulation and tested in real-time scenario. Those data are parsed from beacon listener using TDOA-RSS inverse method. Drone SLAM has nonlinear behavior and for the better precision its applied EKF. IMU and camera odometry with optical flow presents input parameters for EKF block. Initial conditions are focused on KF of drone IMU. Monovision camera odometry is used for optical flow on overall odometry covariance of insecurity.To improve optical flow in covariance of insecurity, it used landmarks on the ground. Specific case scenario of EKF is presented in the paper with drone/listener and beacon positions, which belongs to research area of Range-Only SLAM. Mathematical non-linear expressions are presented between previous position of drone and controlling signal.Initial conditions are arbitrary,while drone elevation is constant.Energy function has been considered to implement in energy optimizing scenario.

Keywords

• particle filter
• tdoa-rss
• ekf
• slam
• optical flow
• energy function