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This paper presents a practical discrete-time consensus-based output-feedback formation control algorithm for quadrotors. A dynamic model is derived by approximating the behaviour of real on-board controllers via system identification, before assuming three decoupled systems to model the longitudinal, lateral and yaw motion. Consensus controllers are designed for all subsystems using discrete-time algebraic Riccati equations and parameter uncertainty theorems with observers suggested for systems without full state information. The performance of the proposed control approach is evaluated through a series of simulation studies and its benefits are shown with real experimental results.

In this letter we identify, and propose a solution for, the string stability problem that may arise in frequency droop control schemes for a type of inverter-based microgrid. We consider a previously proposed frequency droop control with secondary control loop and we investigate the effect on the performance due to an increase in the number of inverters connected to the microgrid. To mitigate the observed performance deterioration, we propose a new controller that guarantees string stability of the inverter-based microgrid and show its performance via simulations.

This article investigates the utility and extension of well-established collision risk modeling approaches for lateral separation standard development for unmanned traffic management and network design. The applicability of standard assumptions and simplifications made in the manned environment to a scaled-down unmanned aerial systems (UAS) environment is first investigated. The results are used to derive an iso-risk surface that shows the tradeoff between separation distance and navigation performance for a given risk level or target level of safety. The model is then extended to consider collision risk from one to (Formula presented.) tracks, and finally to determine the total collision risk and the related iso-risk surfaces for systems of (Formula presented.) parallel tracks with additions to account for the effects of more than two parallel tracks. The extended model is applied to a case study where airspace design for an urban area is conducted via maximization of the number of same-direction parallel tracks while meeting the target level of safety. The results suggest that lateral separation distances less than 100 m are achievable for small UAS, and that the separation standards are mostly affected by the proportion of poorly navigating aircraft.

This paper presents a control design with integral action for vehicle platoons with disturbances that ensures string stability of the closed-loop system and disturbance rejection. The addition of integral action and a coordinate change allows the development of sufficient smoothness conditions on the closed-loop system to ensure that the closed-loop system using the proposed controller is string stable when subject to time-varying disturbances, while rejecting constant disturbances. In addition, bounds for the tracking error of the platoon configuration are also given. A case study is considered together with a suitable controller structure, which satisfies the required smoothness conditions. Simulation results illustrate the performance of the closed-loop system.

This paper presents a cooperative differential game theory approach to designing a consensus-based formation control strategy for multi-UAVs (agents). The consensus-based formation control problem is defined as a tracking task where the states of each agent must follow a given reference. Position states are given as fixed offsets between each agent to achieve a formation, whilst velocity and attitude should be identical amongst agents to archive consensus. Using a cooperative game theory based approach, each agent acts to reduce the weighted team cost to reach consensus. The control strategy design is based on open-loop design, closed-loop design, and a semi-open-loop design concept to better account for different hardware configurations. The control approach is validated via simulations to show how cooperative game theory based consensus formation control can outperform non-cooperative game theory control and general optimal control with respect to reducing formation deviation. The semi-open loop design is proven to be suitable for practical applications.

Aircraft separation standards for manned aircraft are influenced by Required Navigation Performance (RNP) specifications under the Performance Based Navigation concept. Unmanned aircraft operating in a Unmanned Traffic Management (UTM) environment will require separation and thus similar standards need to be derived. This work expands on UTM flight trials conducted in Singapore to characterise the navigation performance of common multi-rotor platforms. Real flight test results enable derivation of the navigation error distributions which are subsequently used to suggest suitable RNP values for the platforms. Additionally, it is found that navigation capability of UAS in close proximity to buildings cannot yet be meaningfully evaluated.

This paper presents the design of an integral controller for vehicle platoons with actuator dynamics. The proposed controller ensures string stability with disturbances and simultaneously compensates for constant disturbances through integral action. Sufficient conditions for string stability are satisfied by the use of a suitable state transformation. The proposed controller guarantees disturbance string stability for a prescribed time constant of the actuator dynamics, and we show through simulation that platoons with faster dynamics are also made disturbance string stable

A method is proposed to extend a feasible trajectory planning technique for thrust vectoring UAV, such that it can be applied to aerial manipulators. This method utilizes high-degree polynomials to calculate the system dynamics that would be necessary to perform a trajectory in a time-constrained manner. The use of this method provides a high quality trajectory that can be used in conjunction with an almost global exponential stable tracking controller. A two-step method is proposed to optimize flight time based on actuator constraints of the system, and allows for flight aggressiveness to be tuned based on a minimal set of parameters.

Navigation in endoscopic environments requires an accurate and robust localisation system. A key challenge in such environments is the paucity of visual features that hinders accurate tracking. This article examines the performance of three image enhancement techniques for tracking under such feature-poor conditions including Contrast Limited Adaptive Histogram Specification (CLAHS), Fast Local Laplacian Filtering (LLAP) and a new combination of the two coined Local Laplacian of Specified Histograms (LLSH). Two cadaveric knee arthroscopic datasets and an underwater seabed inspection dataset are used for the analysis, where results are interpreted by defining visual saliency as the number of correctly matched key-point (SIFT and SURF) features. Experimental results show a significant improvement in contrast quality and feature matching performance when image enhancement techniques are used. Results also demonstrate the LLSHs ability to vastly improve SURF tracking performance indicating more than 87% of successfully matched frames. A comparative analysis provides some important insights useful in the design of vision-based navigation for autonomous agents in feature-poor environments.

This paper introduces the use of discrete-time Markov chain models to represent the spatial-temporal behaviour of air traffic configurations near terminal areas. The airspace is first discretised using a rectangular grid and the occupancy status of each grid cell over each time interval is recorded. Each unique grid occupancy combination is then vectorised to define a unique state. Using the Baum-Welch algorithm, the transition probability between the set of possible states is then determined. Using real air traffic data, the approach is used to model the air traffic behaviour around a large Australian airport. The model is evaluated using hold out data and applied to the novel application of dynamic airspace allocation for integrated unmanned aircraft operations.

This paper considers the problem of automatically determining maximum safe altitudes for unmanned aircraft operating within the aerodrome environment. First, the spatial-temporal behaviour of manned aircraft is modelled at each airspace location defined by a planer polar grid with centre at the aerodrome reference point. Second, an arbitrarily defined vertical separation threshold, unmanned altitude uncertainty and target level of safety (defined as the encounter likelihood) is used to back derive the corresponding maximum safe altitude at each location. Example results are presented for a major Australian aerodrome, including a comparative study with an existing quantitative approach currently considered by regulators. Results highlight the utility of the proposed approach for practical applications that support unmanned traffic management such as automated facility map generation and flight approval.

The system presented is an autonomous multirotor-based aerial manipulator that is capable of searching an environment, visually identifying a payload, and performing a pick-and-place type maneuver. Full 3D trajectories for the search stage of the flight are predefined, with the grasping maneuver generated dynamically once the payload is identified. The manipulator and payload interactions with the multirotor base are actively compensated for by the controller to ensure stable flight during all maneuvers. Experimental results are analyzed to evaluate the performance of the system.

This paper considers the problem of quantifying the vertical overlap probability or vertical collision risk associated with unmanned aircraft operations around aerodromes. The risk models combine real surveillance data and expectations on altitude keeping errors of both manned and unmanned aircraft with well-established collision modelling approaches used in manned aircraft separation standards development. To demonstrate the utility of the proposed vertical collision risk model, a series of investigations are conducted to quantify the vertical collision risk associated with approaching and departing aircraft and the relative impact of unmanned altitude keeping performance. Results demonstrate some shortfalls of current exclusion zones near aerodromes and the need to better understand unmanned navigational errors when considering future unmanned traffic management.

This paper develops and simulates a control scheme to allow for trajectory-based tracking of a multirotor-based aerial manipulator. The approach utilizes a low-level Inverse Dynamics controller that proves suitable for the general case of tree-structured aerial manipulators, and is capable of tracking any arbitrary point on the kinematic tree. Simulation results of common maneuvers for pick-and-place related tasks are presented to assess the performance of the system under varying configurations and trajectories.

The Joint Authority for Rulemaking on UAS (JARUS) recently released a process for managing air and ground risk for Unmanned Aerial Vehicle (UAV) operations: the Specific Operations Risk Assessment (SORA) [1]. This paper focuses on the air risk element, where the challenge of balancing equipment performance for detect and avoid functions against the likelihood they will be needed (encounter rates) is further complicated by safety and costs implications. To date, attempts to achieve this balance have largely been conducted using qualitative measures. The problem with this approach is that it risks superimposing unnecessary cost burdens on industry without transparent evidence it is delivering the perceived safety benefit, or conversely, the process results in under-estimates for encounter rates with inadequate performance standards stipulated. To address this issue, we introduce a Bayesian framework that explicitly links encounter rate exposure, detection performance, cost and safety. We then detail how the framework can be deployed to appropriately match airspace characteristics with suitable equipment performance levels, whilst optimising safety and cost. As part of our testing regime, we identified that a mis-representation of actual traffic encounter rates creates compounding implications for detector performance standards and safety. Accordingly, we incorporate our efforts to characterise a region of Australian airspace, and contrast it with a the qualitative characterisation methods employed within the SORA.

This paper presents the design and implementation of an assisted control technology for a small multirotor platform for aerial inspection of fixed energy infrastructure. Sensor placement is supported by a theoretical analysis of expected sensor performance and constrained platform behaviour to speed up implementation. The optical sensors provide relative position information between the platform and the asset, which enables human operator inputs to be autonomously adjusted to ensure safe separation. The assisted control approach is designed to reduced operator workload during close proximity inspection tasks, with collision avoidance and safe separation managed autonomously. The energy infrastructure includes single vertical wooden poles and crossarm with attached overhead wires. Simulated and real experimental results are provided.