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The purpose of this paper is to review the 2008 AUVSI Conference and Show held in San Diego, California with emphasis on unmanned vehicles or service robots, their application on the ground, in the air and in the water.

The approach takes the form of in‐depth interviews with exhibitors of unmanned vehicles and the providers of the technologies which are fundamental to their design and deployment.

The unmanned robotic vehicle industry is largely driven by government requirements, both military and civilian. Unmanned service robots are also found in commercial applications such as pipeline surveillance, crop monitoring and fish school location at sea.

Developers will be challenged to meet the need for improvements in speed, payload, sensor capabilities, autonomous operation and command and control of fleets of unmanned vehicles.

The paper offers insights into trends and new products in the unmanned robotic vehicle industry.

Unmanned aircraft applications are quickly expanded in different fields. These systems are complex that include several subsystems with different types of technologies. Maintenance and inspection planning is necessary to obtain optimal performance and effectiveness. The failure rate in these systems is more than commercial and manned aircraft since they are usually cheaper. But maintenance and operation planning are difficult because we deal with a system that has multi-components, multi-failure models, and different dependencies between subsystems without any advanced health monitoring system. In this paper, this matter is considered and a framework to determine optimal maintenance and inspection plan for this type of system is proposed to improve system reliability and availability. The new criteria according to this field are proposed.

Maintenance of unmanned systems influences their readiness; also, according to the complexity of the system and different types of components, maintenance programming is a vital requirement. The plan should consider several criteria and disciplines; thus, multicriteria decision approaches may be useful. On another side, the reliability and safety of unmanned aircraft are the most important requirements in the design and operation phases. The authors consider these parameters and develop a framework based on risk-based maintenance to overcome the problems for unmanned systems. This framework consists of two stages: at the first stage, the critical components and failure modes are determined by FMEA, and in the second stage, the priority of maintenance tasks is determined by a fuzzy multicriteria weighted decision system. In this study, fourteen criteria with different levels of importance are developed and proposed to find the best plan for maintenance and inspection intervals. These criteria have been extracted from the literature review, the author's experience, and expert opinions.

A novel framework for risk-based maintenance has been proposed. Risk determination and risk criteria are the most important factors in this framework. Risks are determined by FMEA, and new criteria are proposed that are used for decision-making. These criteria are proposed based on practical experience and experts' opinions for the maintenance process in the aeronautic industry. These are evaluated by industrial cases, and this framework capability has been demonstrated.

The proposed framework and criteria for small unmanned aircraft have been developed based on a practical point of view and expert opinion. Thus for implementation in other aeronautic industries, the framework may need a minor modification.

Two important subsystems of an unmanned aircraft have been studied, and the capabilities of this method have been presented.

This research is original work to determine a maintenance program for unmanned aircraft that their application has rapidly grown up. Practical and design parameters have been considered in this work.

The purpose of this paper is to review the Association for Unmanned Vehicle Systems International (AUVSI) Conference and Show held in Washington DC, with emphasis on unmanned vehicles or service robots and their application on the ground, in the air and in the water.

In‐depth interviews with exhibitors of unmanned vehicles and the providers of the technologies which are fundamental to their design and deployment.

The unmanned vehicle industry is largely driven by government requirements, both military and civilian. Unmanned service robots are also found in applications such as crop monitoring and fish school location at sea. Unmanned vehicles are getting smaller, smarter and more rugged to meet new challenges.

Unmanned vehicles continue to address air, ground and marine application needs where human safety is important. The vehicles continue to become more and more autonomous, smaller and ever better to address a wider range of application requirements.

This paper aims to investigate the possibility of lowering the time taken during the aircraft design for unmanned aerial vehicles by using machine learning (ML) for the configuration selection phase. In this work, a database of unmanned aircraft is compiled and is proposed that decision tree classifiers (DTC) can understand the relations between mission and operational requirements and the resulting aircraft configuration.

This paper presents a ML-based approach to configuration selection of unmanned aircraft. Multiple DTC are built to predict the overall configuration. The classifiers are trained with a database of 118 unmanned aircraft with 57 characteristics, 47 of which are inputs for the classification problem, and 10 are the desired outputs, such as wing configuration or engine type.

This paper shows that DTC can be used for the configuration selection of unmanned aircraft with reasonable accuracy, understanding the connections between the different mission requirements and the culminating configuration. The framework is also capable of dealing with incomplete databases, maximizing the available knowledge.

This paper increases the computational usage for the aircraft design while retaining requirements’ traceability and increasing decision awareness.

Review of the most recent unmanned vehicle show in Washington DC with emphasis on the new robot innovations and applications on display. The paper aims to discuss these issues.

In-depth interviews with exhibitors of unmanned vehicles and suppliers of other related equipment and support services.

Unmanned vehicles are moving rapidly into new applications such as agriculture, environmental monitoring and medical along with maintaining their importance in the traditional military and security applications of the past.

Customers will be surprised at the innovations making these robotic vehicles smaller, smarter and more adaptable to a wide range of new applications.

A review of some of the latest innovations and applications for unmanned vehicles that one might have seen if they had been on the exhibition floor at the most recent Washington DC unmanned vehicle show.

The main purpose of this paper is to investigate the effects of icing on unmanned aerial vehicles (UAVs) at low Reynolds numbers and to highlight the differences to icing on manned aircraft at high Reynolds numbers. This paper follows existing research on low Reynolds number effects on ice accretion. This study extends the focus to how variations of airspeed and chord length affect the ice accretions, and aerodynamic performance degradation is investigated.

A parametric study with independent variations of airspeed and chord lengths was conducted on a typical UAV airfoil (RG-15) using icing computational fluid dynamic methods. FENSAP-ICE was used to simulate ice shapes and aerodynamic performance penalties. Validation was performed with two experimental ice shapes obtained from a low-speed icing wind tunnel. Three meteorological conditions were chosen to represent the icing typologies of rime, glaze and mixed ice. A parameter study with different chord lengths and airspeeds was then conducted for rime, glaze and mixed icing conditions.

The simulation results showed that the effect of airspeed variation depended on the ice accretion regime. For rime, it led to a minor increase in ice accretion. For mixed and glaze, the impact on ice geometry and penalties was substantially larger. The variation of chord length had a substantial impact on relative ice thicknesses, ice area, ice limits and performance degradation, independent from the icing regime.

The implications of this manuscript are relevant for highlighting the differences between icing on manned and unmanned aircraft. Unmanned aircraft are typically smaller and fly slower than manned aircraft. Although previous research has documented the influence of this on the ice accretions, this paper investigates the effect on aerodynamic performance degradation. The findings in this work show that UAVs are more sensitive to icing conditions compared to larger and faster manned aircraft. By consequence, icing conditions are more severe for UAVs.

Atmospheric in-flight icing is a severe risk for fixed-wing UAVs and significantly limits their operational envelope. As UAVs are typically smaller and operate at lower airspeeds compared to manned aircraft, it is important to understand how the differences in airspeed and size affect ice accretion and aerodynamic performance penalties.

Earlier work has described the effect of Reynolds number variations on the ice accretion characteristics for UAVs. This work is expanding on those findings by investigating the effect of airspeed and chord length on ice accretion shapes separately. In addition, this study also investigates how these parameters affect aerodynamic performance penalties (lift, drag and stall).

This paper aims to design the fractional order sliding mode controller for highly maneuverable remote piloted unmanned aircraft with time-varying delays.

With the assumption that the time-varying delays are bounded and identical for different outputs, an observer-based control technique is implied which reformulates the state variables based on the system model and delayed outputs. The estimated state variables are fed as feedback into the controller. Based on the delayed output observer, a fractional order sliding mode controller is designed. Further, the stability of the closed-loop system is analyzed and asymptotical convergence is realized using Lyapunov–Razumikhin theorem.

The simulation is done in Matlab and Simulink. The parametric variations and trajectory tracking results are illustrated which looks propitious.

In practical operation, measurement signal is often delayed, which significantly degrade the control performance or even disturb the stability. It is emphasized to choose attitude as the evaluation indicator for unmanned aerial vehicle time delay.

A novel fractional order sliding mode control technique is designed to enhance the trajectory tracking, thus autonomous flight performance, of the aircraft system. Also, the main idea behind this novel procedure is formulated for minimizing the parametric variations in presence of time delays.

This chapter explores how homeland security agencies can use unmanned aircraft, or drones, as tools to help them perform their public safety missions while earning the support and trust of the communities they serve for the use of this controversial technology. This chapter discusses the applications for drones in public safety and homeland security while also identifying limitations and challenges to their use in government operations. This chapter presents the current state of the law surrounding drone use by government agencies, particularly the police, along with published recommendations on drone implementation and trust-building practices. The author presents the drone-specific recommendations of groups like the International Association of Chiefs of Police, American Civil Liberties Union, and Community Oriented Policing Office of the United States Department of Justice. The author also provides a recommended process to follow for law enforcement and homeland security leaders looking to implement drone programs using evidence-based practices to earn the trust of their citizens.

The purpose of this paper is to describe simulation research carried out for the needs of multi-sensor anti-collision system for light aircraft and unmanned aerial vehicles.

This paper presents an analysis related to the practical possibilities of detecting intruders in the air space with the use of optoelectronic sensors. The theoretical part determines the influence of the angle of view, distance from the intruder and the resolution of the camera on the ability to detect objects with different linear dimensions. It has been assumed that the detection will be effective for objects represented by at least four pixels (arranged in a line) on the sensor matrix. In the main part devoted to simulation studies, the theoretical data was compared to the obtained intruders’ images. The verified simulation environment was then applied to the image processing algorithms developed for the anti-collision system.

A simulation environment was obtained enabling reliable tests of the anti-collision system using optoelectronic sensors.

The integration of unmanned aircraft operations in civil airspace is a serious problem on a global scale. Equipping aircraft with autonomous anti-collision systems can help solve key problems. The use of simulation techniques in the process of testing anti-collision systems allows the implementation of test scenarios that may be burdened with too much risk in real flights.

This paper aims for possible improvement of safety in light-sport aviation.

This paper conducts verification of classic flight simulator software suitability for carrying out anti-collision systems tests and development of a flight simulator platform dedicated to such tests.