Intelligent Autonomous Decision-Making and Cooperative Control Technology of High-Speed Vehicle Swarms

This book is a reprint of the Special Issue “Intelligent Autonomous Decision-Making and Cooperative Control Technology of High-Speed Vehicle Swarms”,which was published in Applied Sciences

Study of operational requirements in hostile and congested areas with unmanned air vehicles (UAV/RPAS)

The target of this study is analyse the operational requirement of UAV/RPAS activities in special conditionsThis study analyses and determines the operational requirements for unmanned aerial vehicles and remotely piloted aircrafts when operating in congested and hostile areas. In order to do so, a study of present regulatory framework from different countries is done and proposals published by regulating authorities from Europe and America as well, concluding this initial approach to unmanned aerial vehicle’s regulations with a benchmark of best practices. Afterwards, a risk analysis and a safe study are done by identifying potential risks, taking into account all possible situations and scenarios that can be produced during an operation in a congested area. Once the risks are adequately identified, an evaluation of them is performed, obtaining as a result a safety level which is acceptable or unacceptable in order to ensure the integrity of people on ground, and consequently developing the operation or not. Finally, for those operations associated to a risk that result in an unacceptable safety level, mitigation measures are proposed to reduce the likelihood of hazard happening and the severity of the consequences. It may be noted that these mitigation measures consist in adding technology to unmanned aircraft systems and establishing operational procedures

Autonomous Approach and Landing Algorithms for Unmanned Aerial Vehicles

In recent years, several research activities have been developed in order to increase the autonomy features in Unmanned Aerial Vehicles (UAVs), to substitute human pilots in dangerous missions or simply in order to execute specific tasks more efficiently and cheaply. In particular, a significant research effort has been devoted to achieve high automation in the landing phase, so as to allow the landing of an aircraft without human intervention, also in presence of severe environmental disturbances. The worldwide research community agrees with the opportunity of the dual use of UAVs (for both military and civil purposes), for this reason it is very important to make the UAVs and their autolanding systems compliant with the actual and future rules and with the procedures regarding autonomous flight in ATM (Air Traffic Management) airspace in addition to the typical military aims of minimizing fuel, space or other important parameters during each autonomous task. Developing autolanding systems with a desired level of reliability, accuracy and safety involves an evolution of all the subsystems related to the guide, navigation and control disciplines. The main drawbacks of the autolanding systems available at the state of art concern or the lack of adaptivity of the trajectory generation and tracking to unpredicted external events, such as varied environmental condition and unexpected threats to avoid, or the missed compliance with the guide lines imposed by certification authorities of the proposed technologies used to get the desired above mentioned adaptivity. During his PhD period the author contributed to the development of an autonomous approach and landing system considering all the indispensable functionalities like: mission automation logic, runway data managing, sensor fusion for optimal estimation of vehicle state, trajectory generation and tracking considering optimality criteria, health management algorithms. In particular the system addressed in this thesis is capable to perform a fully adaptive autonomous landing starting from any point of the three dimensional space. The main novel feature of this algorithm is that it generates on line, with a desired updating rate or at a specified event, the nominal trajectory for the aircraft, based on the actual state of the vehicle and on the desired state at touch down point. Main features of the autolanding system based on the implementation of the proposed algorithm are: on line trajectory re-planning in the landing phase, fully autonomy from remote pilot inputs, weakly instrumented landing runway (without ILS availability), ability to land starting from any point in the space and autonomous management of failures and/or adverse atmospheric conditions, decision-making logic evaluation for key-decisions regarding possible execution of altitude recovery manoeuvre based on the Differential GPS integrity signal and compatible with the functionalities made available by the future GNSS system. All the algorithms developed allow reducing computational tractability of trajectory generation and tracking problems so as to be suitable for real time implementation and to still obtain a feasible (for the vehicle) robust and adaptive trajectory for the UAV. All the activities related to the current study have been conducted at CIRA (Italian Aerospace Research Center) in the framework of the aeronautical TECVOL project whose aim is to develop innovative technologies for the autonomous flight. The autolanding system was developed by the TECVOL team and the author’s contribution to it will be outlined in the thesis. Effectiveness of proposed algorithms has been then evaluated in real flight experiments, using the aeronautical flying demonstrator available at CIRA

Calibration and Extension of a Discrete Event Operations Simulation Modeling Multiple Un-Manned Aerial Vehicles Controlled by a Single Operator

This research improved a simulation that models a single operator responsible for multiple UAV rovers. The improvement calibrated the model by increasing the realism of its expected time that the target will be within the field of view of a UAV\u27s camera and how much of that will be observed by an operator that has multiple tasks to perform throughout the mission. The calibration was derived from multiple flight tests, by using a Field of View Algorithm in MATLAB and by visually recording times for loiter loops by hand. It was determined that the target will be within the field of view of a UAV loitering in a circular pattern between 62% and 66% of the overall loiter time. For an 8 hour beyond line of sight mission, the model\u27s optimal results were 145 min of Value Added Time in low wind conditions and 137 min in high wind. For an 8 hour within line of sight mission, the optimal result was 287 min in low wind conditions and 268 min in high wind

Collision Avoidance and Navigation of UAS Using Vision-Based Proportional Navigation

Electro-optical devices have received considerable interest due to their light weight, low cost, and low algorithm requirements with respect to computational power. In this thesis, vision-based guidance laws are developed to provide sense and avoid capabilities for unmanned aerial vehicles (UAVs) operating in complex environments with multiple static and dynamic collision threats. These collision avoidance guidance laws are based on the principle of proportional navigation (Pro-Nav), which states that a UAV is on a collision course with another vehicle or object if the line-of-sight (LOS) angles to the object remain constant. The guidance laws are designed for use with monocular electro-optical devices, which provide information on the LOS angles to potential collision threats, but not the range. The development of these guidance laws propagates from an investigation into numerous methods of Pro-Nav based guidance, including the use of LOS rate thresholding, avoidance of the most imminent threat detected, and objective-based cost optimization. The collision avoidance guidance laws were applied to nonlinear, six degree-of-freedom UAV models in various simulation environments including a varying number of static and dynamic obstacles. A final form of the avoidance law, determined from these simulation studies, was applied to a small-scale UAV model flying through a virtual urban environment, which utilizes camera-in-the-loop simulation techniques. The final results of these studies showed that the most effective approach was to implement a cost function-based avoidance law that includes a term based on the Pro-Nav intercept heading for a desired waypoint and avoidance terms for all obstacles in view that pose a collision threat. Obstacle avoidance headings in the cost function are based on the difference in the obstacle LOS rates from the magnitude of the minimum safe LOS rate. When applied to UAV simulations in a virtual urban environment, this guidance law provided successful avoidance for the case of a single building, maintained a safe heading through an urban canyon, and determined the safest path through a complex urban layout. For the case of the complex urban layout, a single collision during flight occurred due to a lack of visual feature points to contribute to the avoidance law calculation