Automatic Control & Systems Engineering

1. Automatic Control & Systems Engineering Autonomous Systems Research Uninhabited air vehicles (UAVs) are increasingly being used in areas where manned aircraft are too dangerous, costly or difficult to deploy. In addition to well publicised military applications they can be used in many civilian areas such as search and rescue, monitoring of forest fires, traffic congestion monitoring, aerial surveys, sensing of airborne pollutants, railway track inspection, police and security surveillance. The development of completely autonomous UAVs presents numerous and formidable research challenges. To solve such a challenging systems engineering problem requires a truly multi-disciplinary approach. Researchers in the Department of Automatic Control & Systems Engineering are developing novel intelligent approaches to the design and control of UAVs. Mini-UAV for Urban Environments Future uninhabited air vehicles (UAVs) will increasingly be autonomous, requiring reliable flight control laws for safe operation. This is particularly challenging in urban environments where the UAV will have to operate in enclosed spaces. A number of important applications will require this, e.g. fire and natural disaster search and rescue, police and security services. The aim of this project is to develop a low-cost mini-UAV (MAV) platform suitable for operation in urban environments. A low-cost, fully-autonomous, prototype quadrotor MAV has been developed. This utilises MEMS gyroscopes and accelerometers to provide 6 degree-of-freedom inertial measurements. An autonomous control system is implemented on a microcontroller, the output of which controls the motor speeds providing control in roll, pitch, yaw and vertical displacement. A full Matlab simulation of the quadrotor suitable for control-law prototyping has also been developed together with a Matlab interface for telemetry information. A second-generation quadrotor MAV is now under development. This will utilise a COTS inertial measurement unit, together with a GPS receiver, ultrasonic sensors and stereo-cameras as the primary sensors. These will enable a detailed picture of the urban operating environment to be developed. To provide sufficient processing power the MAV will include dual DSP-FPGA boards for vision processing, sensor fusion and autonomous control. Live telemetry and video will be transmitted over a wireless LAN to a local base station. Four high-powered brushless motors will provide the necessary lift for the approximate 1.5kg mass. The power for the MAV will be provided onboard using lithium polymer batteries. Once the MAV is complete it will provide a test-bed for the development of novel autonomous control algorithms. In particular new sensor fusion algorithms will be developed which combine the disparate sensor types optimally to provide the MAV with situational awareness and operational capability in different urban environments including indoors. Autonomous Control of Multi-UAV Platforms UAV missions will increasingly rely on the use of multiple platforms, requiring autonomous navigation, complex mission planning, task allocation and co-ordination of flight operations. This is particularly true of search and rescue and aerial surveillance applications. The aim of this project is to develop novel algorithms for the simulation and control of multi-UAV platforms. Initial work has focused on adapting an existing aircraft simulation model (ADMIRE) for completely autonomous control. A synthetic flight management tool has been developed which allows flight plans to be input and autonomous control strategies automatically generated. These are based on way-point navigation and use detailed models of aircraft dynamics. Current work is developing this framework to allow for automatic collision avoidance and the simulation of multiple-UAVs over a network of PCs. Future work will focus on developing an intelligent agent-based approach to the autonomous control of multi-UAV platforms. This will take account of wireless communications, models of which will be included in the simulation environment. The algorithms developed in this project will be tested in simulation and also using a group of model helicopters equipped with miniature autopilots developed in house. A fundamental aim of the project is to develop approaches to the autonomous control of multi-UAV platforms which are completely scalable and can therefore be applied to various sizes of UAV platforms. For more information contact: Dr Tony Dodd Department of Automatic Control & Systems Engineering The University of Sheffield Sheffield, UK t.j.dodd@shef.ac.uk