As drones become more widespread throughout modern industry, the demand for drone automation increases. Drones are used for many applications, but their effectiveness relies heavily on their battery life. By designing, implementing, and evaluating an automatic drone landing and battery exchange system, drone missions can be more streamlined and efficient by eliminating the need for manual battery exchange. Previous projects within this topic rely on high-precision landing combined with a manipulator with low degrees of freedom for battery removal. This project offers a solution that allows less strict landing requirements to better fit drones of different sizes and shapes for a wide variety of applications. This autonomous drone landing and battery exchange system uses a robotic arm with 6 degrees of freedom for battery removal and on-board image processing to locate and land on a large, rotatable landing pad.

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Thesis (MScEng)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: This dissertation presents the design and practical demonstration of a flight control system (FCS) that is capable of autonomously landing a fixed-wing, unmanned aerial vehicle (UAV) on a stationary platform aided by a high-precision differential global positioning system. This project forms part of on-going research with the end goal of landing a fixed-wing UAV on a moving platform (for example a ship’s deck) in windy conditions. The main aim of this project is to be able to land the UAV autonomously, safely and accurately on the runway. To this end, an airframe was selected and equipped with an avionics payload. The equipped airframe’s stability derivatives were analysed via AVL and the moment of inertia was determined by the double pendulum method. The aircraft model was developed in such a way that the specific force and moment model (high bandwidth) is split from the point-mass dynamics of the aircraft (low bandwidth) [1]. The advantage of modelling the aircraft according to this unique method, results in a design that has simple decoupled linear controllers. The inner-loop controllers control the high-bandwidth specific accelerations and roll-rate, while the outer-loop controllers control the low-bandwidth point-mass dynamics. The performance of the developed auto-landing flight control system was tested in software-in-the-loop (SIL) and hardware-in-the-loop (HIL) simulations. A Monte Carlo non-linear landing simulation analysis showed that the FCS is expected to land the aircraft 95% of the time within a circle with a diameter of 1.5m. Practical flight tests verified the theoretical results of the developed controllers and the project was concluded with five autonomous landings. The aircraft landed within a circle with a 7.5m radius with the aiming point at the centre of the circle. In the practical landings the longitudinal landing error dominated the landing performance of the autonomous landing system. The large longitudinal error resulted from a climb rate bias on the estimated climb rate and a shallow landing glide slope. / AFRIKAANSE OPSOMMING: Hierdie skripsie stel die ontwikkeling en praktiese demonstrasie van ʼn self-landdende onbemande vastevlerkvliegtuigstelsel voor, wat op ʼn stilstaande platform te lande kan kom met behulp van ʼn uiters akkurate globale posisionering stelsel. Die projek maak deel uit van ʼn groter projek, waarvan die doel is om ʼn onbemande vastevlerkvliegtuig op ʼn bewegende platform te laat land (bv. op ʼn boot se dek) in onstuimige windtoestande. Die hoofdoel van die projek was om die vliegtuig so akkuraat as moontlik op die aanloopbaan te laat land. ʼn Vliegtuigraamwerk is vir dié doel gekies wat met gepaste avionica uitgerus is. Die uitgeruste vliegtuig se aerodinamsie eienskappe was geanaliseer met AVL en die traagheidsmoment is deur die dubbelependulum metode bepaal. Die vliegtuigmodel is op so ‘n manier onwikkel om [1] die spesifieke krag en momentmodel (vinnige reaksie) te skei van die puntmassadinamiek (stadige reaksie). Die voordeel van hierdie wyse van modulering is dat eenvoudige ontkoppelde beheerders ontwerp kon word. Die binnelusbeheerders beheer die vinnige reaksie-spesifieke versnellings en die rol tempo van die vliegtuig. Die buitelusbeheerders beheer die stadige reaksie puntmassa dinamiek. Die vliegbeheerstelsel is in sagteware-in-die-lus en hardeware-in-die-lus simulasies getoets. Die vliegtuig se landingseienskappe is ondersoek deur die uitvoer van Monte Carlo simulasies, die simulasie resultate wys dat die vliegtuig 95% van die tyd binne in ʼn sirkel met ʼn diameter van 1.5m geland het. Praktiese vlugtoetse het bevestig dat die teoretiese uitslae en die prakties uitslae ooreenstem. Die vliegtuig het twee suksesvolle outomatiese landings uitgevoer, waar dit binne ʼn 7.5m-radius sirkel geland het, waarvan die gewenste landingspunt die middelpunt was. In die outomatiese landings is die longitudinale landingsfout die grootse. Die groot longitudinale landingsfout is as gevolg van ʼn afset op die afgeskatte afwaartse spoed en ʼn lae landings gradiënt.

We present a method of performing precision landings of a vertical take-off and landing (VTOL) unmanned air vehicle (UAV) with the use of an onboard vision sensor and information about the aircraft's orientation and altitude above ground level (AGL). A method for calculating the 3-dimensional location of the UAV relative to a ground target of interest is presented as well as a navigational controller to position the UAV above the target. A method is also presented to prevent the UAV from moving in a way that will cause the ground target of interest to go out of view of the UAV's onboard camera. These methods are tested in simulation and in hardware and resulting data is shown. Hardware flight testing yielded an average position estimation error of 22 centimeters. The method presented is capable of performing precision landings of VTOL UAV's with submeter accuracy.

In this thesis two methods were developed for precise maritime landing of an autonomous multirotor aircraft based on real-time kinematic (RTK) Global Navigation Satellite System (GNSS). The first method called RTK-localized method (RLM) uses RTK GNSS measurements to localize a sea vessel and execute the landing. RLM was demonstrated outdoors in hardware and landed on a physically simulated boat called a mock-boat with an average landing error of 9.7 cm. The mock-boat was actuated to have boat-like motion and a forward velocity of ~2 m/s. This method showed that accurate landing is possible with RTK GNSS as the primary means of localizing a sea vessel. The localization was unaided by non-GNSS sensors or an estimator, but lacked full attitude estimation and measurement smoothing. The second method was called RTK-Estimation Method (REM) and provides a more complete and robust solution, particularly at sea. It includes a base (landing pad) estimator to fuse RTK GNSS measurements with a dynamic model of a sea vessel. In contrast to RLM, the estimator provides full attitude estimation and measurement smoothing. The base estimator consists of an EKF in conjunction with a complimentary filter and estimates the relative position, attitude, and velocity of a moving target using RTK GNSS and inertial measurements alone. REM was demonstrated outdoors in hardware for 18 flight tests. The same mock-boat from RLM was used as a substitute for a sea vessel, and the boat motion varied between tests. These dynamics were recorded and performances were compared. The rate of success was high given moderate mock-boat motion and degraded with more aggressive motion. Tests were conducted with forward velocities from 0 to 3 m/s and moderate to high wave like motion. Over all tests for REM, the multirotor landed with an average accuracy of 12.7 cm. The methods described depart from common methods given that the only sensors involved for tracking the sea vessel were RTK GNSS receivers and inertial measurement units. Most current methods rely on computer vision, and can fail in poor lighting conditions, in the presence of ocean spray, and other scenarios. The given solutions do not fail under such conditions. The multirotor was equipped with a standard off-the-shelf autopilot, PX4, and the methods function with common control and estimation schemes. The two methods are capable of landing on relatively small landing pads, on the order of 1 m by 1 m, at sea using measurements from satellites thousands of kilometers away.

Precision landing capability is a necessary development that must take place before unmanned aircraft systems (UAS) can realize their full potential in today's modern society. Current multirotor UAS are heavily reliant on GPS data to provide positioning information for landing. While generally accurate to within several meters, much higher levels of accuracy are needed to ensure safe and trouble-free operations in several UAS applications that are currently being pursued. Examples of these applications include package delivery, automatic docking and recharging, and landing on moving vehicles. The specific problem we consider is that of precision landing of a multirotor unmanned aircraft on a small barge at sea---which presents several significant challenges. Not only must we land on a moving vehicle, but the vessel also experiences random rotational and translational motion as a result of waves and wind. Because maritime operations often span long periods of time, it is also desirable that precision landing can occur at any time---day or night.In this work we present a complete approach for precision shipboard landing and address each of the aforementioned challenges. Our method is enabled by leveraging an on-board camera and a specialized landing target which can be detected in light or dark conditions. Features belonging to the target are extracted from camera imagery and are used to compute image-based visual servoing velocity commands that lead to precise alignment between the multirotor and landing target. To enable the multirotor to match the horizontal velocities of the barge, an extended Kalman filter is used to generate feed-forward velocity reference commands. The complete landing procedure is guided by a state machine architecture that incorporates corrections to account for wind, and is also capable of quickly reacquiring the landing target in a loss event. Our approach is thoroughly validated through full-scale outdoor flight tests and is shown to be reliable, timely, and accurate to within 4 to 10 centimeters.

Two flash lidars, integrated from a number of cutting-edge components from industry and NASA, are lab characterized and flight tested under the Autonomous Landing and Hazard Avoidance (ALHAT) project (in its fourth development and field test cycle) which is seeking to develop a guidance, navigation, and control (GNC) and sensing system based on lidar technology capable of enabling safe, precise human-crewed or robotic landings in challenging terrain on planetary bodies under any ambient lighting conditions. The flash lidars incorporate pioneering 3-D imaging cameras based on Indium-Gallium-Arsenide Avalanche Photo Diode (InGaAs APD) and novel micro-electronic technology for a 128 x 128 pixel array operating at 30 Hz, high pulse-energy 1.06 ?m Nd:YAG lasers, and high performance transmitter and receiver fixed and zoom optics. The two flash lidars are characterized on the NASA-Langley Research Center (LaRC) Sensor Test Range, integrated with other portions of the ALHAT GNC system from around the country into an instrument pod at NASA-JPL, integrated onto an Erickson Aircrane Helicopter at NASA-Dryden, and flight tested at the Edwards AFB Rogers dry lakebed over a field of human-made geometric hazards. Results show that the maximum operational range goal of 1000m is met and exceeded up to a value of 1200m, that the range precision goal of 8 cm is marginally met, and that the transmitter zoom optics divergence needs to be extended another eight degrees to meet the zoom goal 6° to 24°. Several hazards are imaged at medium ranges to provide three-dimensional Digital Elevation Map (DEM) information. / Master of Science