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The purpose of this paper is to review the 2007 AUVSI Conference and Show held in Washington DC with emphasis on unmanned vehicles or service robots, 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. Also, attendance at conference presentations.

The unmanned 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 vehicle industry.

The purpose of this paper is to present a review of the AUVSI Conference and Show held in Orlando, FL with emphasis on unmanned vehicles or service robots, their application on the ground, in the air and in the water.

The paper is based on in‐depth interviews with exhibitors of unmanned vehicles and the providers of the technologies which are fundamental to their design and deployment, as well as attendance at conference presentations.

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.

Robot builders need to continue to develop specialized robots and tooling to match with advancements in applications in the plastic industry. Users will need to think of robots as a necessary adjunct to any injection molding application.

The paper offers insights into the unmanned vehicle industry.

The purpose of this paper is to review the 2009 AUVSI Conference and Show held in Washington, DC with emphasis on unmanned vehicles or service robots, their application on the ground, in the air, and in the water.

The paper is 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.

The purpose of this paper is to review the most recent AUVSI unmanned vehicle show, with emphasis on the new robot innovations and applications on display.

In‐depth interviews with exhibitors of unmanned vehicles.

Unmanned vehicles are being coming more autonomous and addressing an ever‐increase range of applications in military, law enforcement, and commercial applications such as agriculture, fishing and rescue operations.

Customers will have to begin thinking of unmanned vehicle robots and able body helpers in all kinds of applications.

The paper presents a review of the latest innovations that one might have seen if they had been on the exhibition floor at the Las Vegas unmanned show.

The purpose of this paper is to review recent developments in sensors for application in unmanned vehicles.

This study included in-depth interviews with exhibitors of sensors and sensor integrators at trade shows and contact with providers of such devices to the industry.

Sensor innovation has made giant leaps in producing much smaller and smarter sensors to address unmanned vehicle requirements.

Developers of unmanned vehicles of all types may be surprised at the sensor innovations and new applications to which sensors are being applied in this rapidly advancing field.

A review of some of the latest sensor innovations and applications that one might have seen if they had been on the exhibition floor at the recent trade shows, followed industrial publications or announcements from sensor developers.

To avoid this situation, the authors proposed an optimal artificial bee colony algorithm-based Unmanned Aerial Vehicle (UAV) routing algorithm for efficient data communication between doctors and patients. This proposed method worked in three stages.

In recent decades, wireless body area networks have played an important role in health care applications. It facilitates the transmission of the patients' health data analysis report to the appropriate doctors.

In the first phase, biological sensors are connected to the human body via a controller node and collected data is transmitted via Bluetooth to the Personal Device Assistant (PDA). In the second phase, collected data will be transmitted via the Internet of things using an artificial bee colony algorithm. The second aids in determining the best route. In the third phase, unmanned aerial vehicles will use the best path to send collected data to doctors, caregivers, ambulances and cloud storage servers.

The simulation results show that the network's performance is superior when compared to existing approaches. The proposed algorithm achieves a high throughput, a lower delay, a higher link rate and a higher delivery rate.

Since many global path planning algorithms cannot achieve the planned path with both safety and economy, this study aims to propose a path planning method for unmanned vehicles with a controllable distance from obstacles.

First, combining satellite image and the Voronoi field algorithm (VFA) generates rasterized environmental information and establishes navigation area boundary. Second, establishing a hazard function associated with navigation area boundary improves the evaluation function of the A^* algorithm and uses the improved A^* algorithm for global path planning. Finally, to reduce the number of redundant nodes in the planned path and smooth the path, node optimization and gradient descent method (GDM) are used. Then, a continuous smooth path that meets the actual navigation requirements of unmanned vehicle is obtained.

The simulation experiment proved that the proposed global path planning method can realize the control of the distance between the planned path and the obstacle by setting different navigation area boundaries. The node reduction rate is between 33.52% and 73.15%, and the smoothness meets the navigation requirements. This method is reasonable and effective in the global path planning process of unmanned vehicle and can provide reference to unmanned vehicles’ autonomous obstacle avoidance decision-making.

This study establishes navigation area boundary for the environment based on the VFA and uses the improved A* algorithm to generate a navigation path that takes into account both safety and economy. This study also proposes a method to solve the redundancy of grid environment path nodes and large-angle steering and to smooth the path to improve the applicability of the proposed global path planning method. The proposed global path planning method solves the requirements of path safety and smoothness.

The purpose of this paper is to propose a control approach for small unmanned helicopters, and a novel swarm intelligence algorithm is used to optimize the parameters of the proposed controller.

Small unmanned helicopters have many advantages over other unmanned aerial vehicles. However, the manual operation process is difficult because the model is always instable and coupling. In this paper, a novel optimized active disturbance rejection control (ADRC) approach is presented for small unmanned helicopters. First, a linear attitude model is built in hovering condition according to small perturbation linearization. To realize decoupling, this model is divided into two parts, and each part is equipped with an ADRC controller. Finally, a novel Levy flight-based pigeon-inspired optimization (LFPIO) algorithm is developed to find the optimal ADRC parameters and enhance the performance of controller.

This paper applies ADRC method to the attitude control of small unmanned helicopters so that it can be implemented in practical flight under complex environments. Besides, a novel LFPIO algorithm is proposed to optimize the parameters of ADRC and is proved to be more efficient than other homogenous methods.

The model of proposed controller is built in the hovering action, whereas it cannot be used in other flight modes.

The optimized ADRC method can be implemented in actual flight, and the proposed LFPIO algorithm can be developed in other practical optimization problems.

ADRC method can enhance the response and robustness of unmanned helicopters which make it valuable in actual environments. The proposed LFPIO algorithm is proved to be an effective swarm intelligence optimizer, and it is convenient and valuable to apply it in other optimized systems.

To demonstrate proof‐of‐concept of the Griffon man‐portable hybrid unmanned ground vehicle/unmanned aerial vehicle (UGV/UAV) based on the iRobot PackBot we developed the Griffon air mobility system consisting of a gasoline‐powered propeller engine, a steerable parafoil, and a radio‐controlled servo system. We integrated the AMS with a PackBot prototype, and we conducted ground and flight tests to validate this concept. The Griffon prototype was capable of remote‐controlled flight, take‐off, and landing. The Griffon achieved speeds of over 20 mph and altitudes of up to 200 feet. We demonstrated the feasibility of developing a man‐portable hybrid UGV/UAV. Future work may explore the possibilities for teleoperated, semi‐autonomous, and fully autonomous control using the Griffon concept. The parafoil wing limits the usability of this vehicle in windy conditions, but this could be addressed using a lightweight fixed wing instead. Man‐portable hybrid UGV/UAVs may be used by the military to perform reconnaissance and strike missions in urban environments, and by civilian teams to conduct search‐and‐rescue operations in hazardous terrain. This research provides the first demonstration of a man‐portable unmanned vehicle capable of both flight and ground locomotion, and it does so using a combat‐tested UGV platform.