Towards an autonomous vision-based unmanned aerial system againstwildlife poachers

Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing.Peer Reviewe

Autonomous deployment and repair of a sensor network using an unmanned aerial vehicle

We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as large-scale environmental monitoring or for command and control in emergency situations. We describe in detail the algorithms used for deployment and for measuring network connectivity and provide experimental data we collected from field trials. A particular focus is on determining gaps in connectivity of the deployed network and generating a plan for a second, repair, pass to complete the connectivity. This project is the result of a collaboration between three robotics labs (CSIRO, USC, and Dartmouth.)

Towards an autonomous vision-based unmanned aerial system against wildlife poachers.

Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $ 213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing

Accurate navigation applied to landing maneuvers on mobile platforms for unmanned aerial vehicles

Drones are quickly developing worldwide and in Europe in particular. They represent the future of a high percentage of operations that are currently carried out by manned aviation or satellites. Compared to fixed-wing UAVs, rotary wing UAVs have as advantages the hovering, agile maneuvering and vertical take-off and landing capabilities, so that they are currently the most used aerial robotic platforms. In operations from ships and boats, the final approach and the landing maneuver are the phases of the operation that involves a higher risk and where it is required a higher level of precision in the position and velocity estimation, along with a high level of robustness in the operation. In the framework of the EC-SAFEMOBIL and the REAL projects, this thesis is devoted to the development of a guidance and navigation system that allows completing an autonomous mission from the take-off to the landing phase of a rotary-wing UAV (RUAV). More specifically, this thesis is focused on the development of new strategies and algorithms that provide sufficiently accurate motion estimation during the autonomous landing on mobile platforms without using the GNSS constellations. In one hand, for the phases of the flights where it is not required a centimetric accuracy solution, here it is proposed a new navigation approach that extends the current estimation techniques by using the EGNOS integrity information in the sensor fusion filter. This approach allows improving the accuracy of the estimation solution and the safety of the overall system, and also helps the remote pilot to have a more complete awareness of the operation status while flying the UAV In the other hand, for those flight phases where the accuracy is a critical factor in the safety of the operation, this thesis presents a precise navigation system that allows rotary-wing UAVs to approach and land safely on moving platforms, without using GNSS at any stage of the landing maneuver, and with a centimeter-level accuracy and high level of robustness. This system implements a novel concept where the relative position and velocity between the aerial vehicle and the landing platform can be calculated from a radio-beacon system installed in both the UAV and the landing platform or through the angles of a cable that physically connects the UAV and the landing platform. The use of a cable also incorporates several extra benefits, like increasing the precision in the control of the UAV altitude. It also facilitates to center the UAV right on top of the expected landing position and increases the stability of the UAV just after contacting the landing platform. The proposed guidance and navigation systems have been implemented in an unmanned rotorcraft and a large number of tests have been carried out under different conditions for measuring the accuracy and the robustness of the proposed solution. Results showed that the developed system allows landing with centimeter accuracy by using only local sensors and that the UAV is able to follow a mobile landing platform in multiple trajectories at different velocities