Visual Simultaneous Localization and Mapping Using Direct-Based Method for Unmanned Aerial Vehicle (UAV)

The Direct Sparse Odometry (DSO) technique is a new form of visual odometry that makes use of a direct and sparse structure to achieve precision. In this project, the objective is to apply the DSO algorithm on the Unmanned Aerial Vehicle (UAV) application. The main studies in this project are focusing on the experimentation for DSO algorithm parameter setting. Another objective is to evaluate the parameter and performance of DSO algorithm. The data evaluation was based on three different environments in the university campus. In this project, the Realsense D435i camera was applied to the RDDRONE-FMUK66 with interface of the Raspberry Pi 3 B+ model to capture the data. This project managed to analyze suitable point values on the active points and gradient parameter setting. The same parameter configuration which concerns on point density and keyframe management have been experimented in the three environment. From this project it is concluded that DSO on UAV can be improved in order to gain a stable data processing to be applied in the algorithm

IRFOC induction motor with rotor time constant estimation modelling and simulation

Purpose– To provide a new and simple inverse rotor time constant identification method which can be used to update an indirect rotor field oriented controlled (IRFOC) induction motor algorithm.Design/methodology/approach– Two different equations are used to estimate the rotor flux in the stator reference frame. One of the equations is a function of the rotor time constant, rotor angular velocity and the stator currents. The other equation is a function of measured stator currents and voltages. The equation that uses the voltage and the current signals of the stator serves as reference model, however, the other equation works as an adjustable model with respect to the variation of the rotor time constant. Voltage signals used in the reference model equation are obtained from the measured DC bus voltage and the inverter gating signals. The proposed scheme is verified using a MATLAB/SIMULINK model for two different motors and experimentally using a DSP development tool (MCK 243) supplied by Technosoft S.A.Findings– The proposed estimator was able to successfully track the actual value of the inverse rotor time constant for different load torque and speed operating conditions. Increased oscillations in the estimated inverse rotor time constant appeared at lower speeds (below 10 per cent of rated speed) due to drift in a PI regulator (used at the estimator side), which was tuned under rated operating conditions and using parameters nominal values.Research limitations/implications– This estimation scheme is limited when near zero speed operation is demanded; otherwise it gives a simple and practical solution. A suggested way out of this, is to provide a self‐tuning controller that can automatically adjust even for zero speed operation, or to automatically disconnect the estimator and take the most updated value as long as the operating speed is below a predetermined value.Originality/value– This paper presented a new inverse rotor time constant estimator for an IRFOC induction motor application and in conjunction rotor flux was estimated without voltage phase sensors