Coordinated motion of UGVs and a UAV

Coordination of autonomous mobile robots has received significant attention during the last two decades. Coordinated motion of heterogenous robot groups are more appealing due to the fact that unique advantages of different robots might be combined to increase the overall efficiency of the system. In this paper, a heterogeneous robot group composed of multiple Unmanned Ground Vehicles (UGVs) and an Unmanned Aerial Vehicle (UAV) collaborate in order to accomplish a predefined goal. UGVs follow a virtual leader which is defined as the projection of UAV’s position onto the horizontal plane. The UAV broadcasts its position at certain frequency. The position of the virtual leader and distances from the two closest neighbors are used to create linear and angular velocity references for each UGV. Several coordinated tasks have been presented and the results are verified by simulations where certain amount of communication delay between the vehicles is also considered. Results are quite promising

UAV based group coordination of UGVs

Coordination of autonomous mobile robots has received significant attention during the last two decades with the emergence of small, lightweight and low power embedded systems. Coordinated motion of heterogenous robots is important due to the fact that unique advantages of di erent robots might be combined to increase the overall task efficiency of the system. In this thesis, a new coordination framework is developed for a heterogeneous robot system, composed of multiple Unmanned Ground Vehicles (UGVs) and an Unmanned Aerial Vehicle (UAV), that operates in an environment where individual robots work collaboratively in order to accomplish a predefined goal. UAV, a quadrotor, detects the target in the environment and provides a feasible trajectory from an initial configuration to a final target location. UGVs, a group of nonholonomic wheeled mobile robots, follow a virtual leader which is created as the projection of UAV's 3D position onto the horizontal plane. The UAV broadcasts its position at certain frequency to all UGVs. Two different coordination models are developed. In the dynamic coordination model, reference trajectories for each robot is generated from the motion of nodal masses located at each UGV and connected by virtual springs and dampers. Springs have adaptable parameters that allow the desired formation to be achieved In the kinematic coordination model, the position of the virtual leader and distances from the two closest neighbors are directly utilized to create linear and angular velocity references for each UGV. Several coordinated tasks are presented and the results are verified by simulations where different number of UGVs are employed and certain amount of communication delays between the vehicles are also considered. Simulation results are quite promising and form a basis for future experimental work on the topic

Multi-robot relative localisation using computer vision

This thesis focusses on robots with a marsupial relationship that use computer vision as their main sensor. This work is focused on two separate projects. In computer vision, drift is still a major drawback when using vision-based localisation methods. The first project of this thesis combines the position information from two Unmanned Ground Vehicles (UGV) to reduce this drift in GPS denied environments. Relative pose measurements between two robots are used in a similar way to loop-closure. The robots start at a nearby location and share a common field of view. The sharing of the information is done periodically. The pose of each robot is calculated using visual odometry. The relative position of the robots is calculated using both monocular and stereo image pairs, for initial estimation and refining respectively. A specific algorithm is proposed to combine the visual odometry and relative pose estimations from one robot to another in a pose graph optimisation scheme to reduce the drift. Experiments have been conducted on both simulations and real-life. The second project introduces two new methods that enabled the autonomous take-off, tracking and precise landing with an Unmanned Aerial Vehicle (UAV) on a UGV using a dual monocular camera setup. These methods used predefined markers to compute the relative position of the UAV from the landing platform that is attached to the UGV. The cameras on the UAV have different focal lengths, which are providing better performance than using a single camera. Different markers and detectors pairs are analysed and compared to achieve a reliable pose estimation. For a UAV, the most critical parts of the flight are take-off and landing, as this is the time most prone to crashes. Two methods are proposed, named as'Landing calibration' and "Marker Connector", that helped the UAV to land precisely at the desired position in a GPS denied environment. Each method has been verified with more than hundred real-world experiments.Doctor of Philosoph

MAGNETIC ACTUATION OF NANOFLUIDS WITH FERROMAGNETIC PARTICLES

ABSTRACT Electromagnetically actuated microflows are generated by using ferromagnetic nanofluids containing Fe 2 O 3 based nanoparticles. Because of their magnetic properties these nanoparticles are able to response to a magnetic field imposed along a microchannel so that a microflow could be driven. Nanofluid samples were located inside a minichannel and were directed with a magnetic field, which was induced by a solenoid wrapped around the minichannel, to drive the flow inside the minichannel, where its flow rate was also recorded. The flow rate was measured as a function of the imposed magnetic field. The corresponding pressure drop to deliver the same flow rate with an ordinary pump along the same minichannel was estimated so that the potential of this system for acting as a micropump in microfluidic applications was revealed

Magnetic actuation of nanofluids with ferromagnetic particles

Electromagnetically actuated microflows are generated by using ferromagnetic nanofluids containing Fe2O3 based nanoparticles. Because of their magnetic properties these nanoparticles are able to response to a magnetic field imposed along a microchannel so that a microflow could be driven. Nanofluid samples were located inside a minichannel and were directed with a magnetic field, which was induced by a solenoid wrapped around the minichannel, to drive the flow inside the minichannel, where its flow rate was also recorded. The flow rate was measured as a function of the imposed magnetic field. The corresponding pressure drop to deliver the same flow rate with an ordinary pump along the same minichannel was estimated so that the potential of this system for acting as a micropump in microfluidic applications was revealed