This paper will present an overview of indoor and outdoor drone localization methods. Outdoor scenarios almost always use a GPS with IMU. Indoor systems are using short-range sensors that are sensitive to the external conditions of the environment. Mostly used methods are optical flow and stereovision, while an ultrasonic transceiver system optimizes and provides high precision and orientation of the drone. An ultrasonic preceptor is integrated into a listener/beacon and can be used with referenced beacons inside a WSN. The Crossbow Cricket hardware platform, which is based on TDOA and RSS principle, is used for simulations and code development. The researched direction is the localization of referent nodes (beacons) concerning the listener which is mounted on a flying drone. For that purpose, a probabilistic approach is used, based on a Bayes filter, where the positions of the beacon can be observed like random variables. Considering that these distributions significantly vary from a Gauss distribution, it is appropriate to use a particle filter.
One of the most important issues in wireless sensor networks (WSN) is reduction of power consumption, prolonging the network lifetime (for battery powered networks) or reducing the induced CO 2 emissions (for grid powered networks). Power consumption reduction can be achieved in various ways: transmitter power control, duty cycling, data reduction and others. This paper analyses the impact of several parameters on power consumption of Digi's XBee PRO of shelf WSN modules. To determine the conditions for transmitter power control, this paper presents measurement analysis for indoor RF propagation in order to determine the minimum received signal strength for high data transfer reliability. Measurement analysis is conducted using response surface methodology and the conclusions based on the respective measurement results are given resulting in a mathematical model of the node's power consumption. Also, optimization of power consumption is shown for various parameters using desirability functions, where optimal parameters for minimum power consumption are presented.
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 controling signal.Initial conditions are arbitrary,while drone elevation is constant.Energy function has been considered to implement in energy optimizing scenario.
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