Quality-sensitive foraging by a robot swarm through virtual pheromone trails

Large swarms of simple autonomous robots can be employed to find objects clustered at random locations, and transport them to a central depot. This solution offers system parallelisation through concurrent environment exploration and object collection by several robots, but it also introduces the challenge of robot coordination. Inspired by ants’ foraging behaviour, we successfully tackle robot swarm coordination through indirect stigmergic communication in the form of virtual pheromone trails. We design and implement a robot swarm composed of up to 100 Kilobots using the recent technology Augmented Reality for Kilobots (ARK). Using pheromone trails, our memoryless robots rediscover object sources that have been located previously. The emerging collective dynamics show a throughput inversely proportional to the source distance. We assume environments with multiple sources, each providing objects of different qualities, and we investigate how the robot swarm balances the quality-distance trade-off by using quality-sensitive pheromone trails. To our knowledge this work represents the largest robotic experiment in stigmergic foraging, and is the first complete demonstration of ARK, showcasing the set of unique functionalities it provides

RFID based navigation for autonomous vehicles

In dieser Arbeit wurden die Möglichkeiten eines pheromonbasierten Navigationsverfahrens mittels wiederbeschreibbarer RFID-Tags untersucht. Im Gegensatz zu anderen Ansätzen wird hier auf eine eindeutige Fahrzeuglokalisierung verzichtet. Es wurden Algorithmen für die Navigation entwickelt und in einem Test-System evaluiert. Um eine höhere Fahrgeschwindigkeit zu erreichen, wurden Antikollisionsalgorithmen für das Inventory optimiert. Des Weiteren wurde ein neuer Inventory-Ansatz ausgearbeitet, der insbesondere für die untersuchten Navigationssysteme geeignet ist.In this thesis the possibilities of a pheromone-based navigation system using rewritable RFID tags have been examined. In contrast to other approaches, this system does not make use of an unambiguous localisation of vehicles. Navigation algorithms have been developed and evaluated in a test system. In order to achieve a higher driving speed, the optimisation of current anti-collision algorithms was necessary. Furthermore, a new inventory approach has been introduced, which has strengths in the examined navigation systems

Approaches to fast sequential inventory and path following in RFID-enriched environments

Abstract: Although RFID is mostly used for ticketing, e-passports and supply chain management applications, the technology is also suitable for transponder based navigation systems. There it can be applied to leave a virtual trace on writeable RFID tags. These applications use RFID in a different way, because the tags are stationary and related to each other, since each tag of the path points to the following one. This offers the possibility to develop more efficient algorithms for their detection. In this paper, we suggest to store the identifying masks of subsequent tag IDs on the tags. The approach can easily be used with query-tree anti-collision methods. We examine the requirements for such an approach and describe a concrete algorithm, which is simulated and compared with different anti-collision algorithms