Robot Formation Control Methodology based on Artificial Vector Fields
|Hauptberichter:||Prof. Dr.-Ing. Joachim Horn|
|Tag der mündlichen Prüfung:||15.08.2017|
Kurzfassung auf Englisch:
Formation control has been one of the important topics covered in the researches on the multi-agent systems. The applications of the multi-agent systems are significant in variety of tasks such as search and rescue missions, forest fire detection, reconnaissance, surveillance, etc. Inspired by the cooperative ability as well as the intelligence of natural animal groups such as schools of fishes, flocks of birds, swarm of ants, etc., this dissertation develops the artificial vector field method for formation control of autonomous robots while tracking one or more moving targets in a dynamic environment. In our approach, the proposed artificial vector fields, which consist of the attractive, repulsive, and rotational force field, are combined with the damping term in the formation control laws in order to control the velocity, heading, connectivity, as well as the obstacle avoidance of a swarm of autonomous robots while in motion. Using this approach, autonomous robots are not only controlled to move along a desired trajectory towards the target, but are also held in a specified formation without collisions during movement. In other words, under the effects of the proposed artificial vector fields, the member robots of a swarm will move together in a specified formation with the velocity matching, without collisions among them while tracking the target. In addition, the free robots will themselves approach the created formation from their swarm in order to obtain the fixed position in this formation. Especially, the thesis then explains that by using the proposed hybrid force field in the obstacle avoiding controller, the local minima problems that still exist in the traditional potential field method (for example, when a robot is trapped in U-shape obstacle, etc.) will be solved. In the proposed hybrid force field, the local repulsive force field surrounding obstacles, which is stronger when the robot is closer to the obstacles, is utilized to repel the robot away from the obstacles, while a local rotational force field is added to surround the obstacles in order to drive robot to escape the obstacles in the direction of the target’s trajectory. Therefore, robots can easily and quickly avoid obstacles, as well as escape complex obstacles along their moving trajectory in order to complete the assigned tasks with their swarm. The thesis focuses on two main issues in formation control, namely, (i) formation control following the desired formations and (ii) cooperative formation control. The first issue concerns how robots are controlled by the proposed formation control algorithm in order to approach the coordinated virtual nodes in the desired formation (for example, Vshape, line or circular shape), and to maintain following these virtual nodes during tracking; while the second issue showcases the use of the proposed cooperative formation control law, where robots will automatically cooperate with each other in their neighboring relationship in order to generate and maintain the cohesion in their formation.
Kurzfassung auf Englisch:
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