Browsing by Author "Grobler, Reghard"
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- ItemAutomated recharging and vision-based improved localisation for a quadrotor UAV(Stellenbosch : Stellenbosch University, 2021-03) Grobler, Reghard; Jordaan, Hendrik Willem; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: In the growing field of autonomous multirotor unmanned aerial vehicles (UAVs) applications, one of the biggest challenges to achieving full autonomy is the limited flight duration. While improvements to existing battery technology is on the way, a solution is required to allow any UAV to perform self recharging without any human intervention and indefinitely increase any mission duration. Such a system could potentially unlock more UAV applications which currently seem impractical. This could allow UAVs to autonomously perform any task in remote locations and extend the radius of operation to far beyond what is currently possible. This thesis presents an autonomous recharging solution which involves a UAV performing an accurate vision based autolanding on a custom charging platform prior to charging. A direct contact approach design is proposed which makes use of onboard electrodes and charging pads located on the charging platform for electrical energy transfer. This system is designed to enable any UAV to self recharge with zero human intervention. A quadrotor UAV was built for the purpose of practically demonstrating the proposed solution. A Pixhawk flight controller using PX4 was chosen as the avionics of the vehicle. Custom controller gains were designed for the UAV in order to satisfy the desired flight characteristic requirements. An autonomous vision based autolanding strategy for this vehicle was designed and simulated using software-in-the-loop (SITL) and hardware-in-the-loop (HITL) simulations in Gazebo simulator. This allowed for the actual PX4 flight control software to be executed on an accurate simulated model of the UAV prior to practical flight tests. A ROS package was developed for the autolanding which was responsible for image processing, publishing control setpoints and processed visual feedback data to the flight controller for accurate control during the autolanding. An average landing accuracy of 4cm was achieved in practical flight tests using this strategy. In many UAV applications highly accurate localisation of the UAV is required which is unachievable using traditional Global Navigation Satellite System (GNSS). This thesis presents a solution which involves using the charging stations as visual landmarks in order to localise the UAV. A marker based Simultaneous Localisation and Mapping (SLAM) strategy is implemented which aims to map the charging stations in the inertial frame while simultaneously localising the UAV within the same reference frame. The SLAM output is published to the flight controller where it is included in the UAV’s state estimation process using PX4’s EKF2. Simulation and practical results are provided which showed that the localisation accuracy could be greatly improved provided that the stations were accurately mapped and that the stations were clearly visible.