Localized communication in swarms has been shown to increase swarm effectiveness in some situations by allowing for additional opportunities for cooperation. However, communication and utilization of potentially outdated information is also a concern. We present an explicit non-directional goal-based communication model and message accept reject scheme, and test our model in a set of object gathering experiments with a swarm of robots. The results of the experiments indicate that even low levels of communication regarding the swarm's goal outperform high levels of random information communication.
This paper proposes several designs for a reliable infra-red based communication techniques for swarm robotic applications. The communication system was deployed on an autonomous miniature mobile robot (AMiR), a swarm robotic platform developed earlier. In swarm applications, all participating robots must be able to communicate and share data. Hence a suitable communication medium and a reliable technique are required. This work uses infrared radiation for transmission of swarm robots messages. Infrared transmission methods such as amplitude and frequency modulations will be presented along with experimental results. Finally the effects of the modulation techniques and other parameters on collective behavior of swarm robots will be analyzed. Until his death in 1982, Karl von Frisch was the world's most renowned authority on bees. "The Dance Language and Orientation of Bees" is his masterwork - the culmination of more than fifty years of research. Now available for the first time in paperback, it describes in non-technical language what he discovered in a lifetime of study about honeybees - their methods of orientation, their sensory faculties, and their remarkable ability to communicate with one another. Thomas Seeley's new foreword traces the revolutionary effects of von Frisch's work, not just for the study of bees, but for all subsequent research in animal behaviour. This new paperback edition also includes a "Personal Appreciation" of von Frisch by the distinguished biologist Martin Lindauer, who was von Frisch's protege and later his colleague and friend. Communication is often required for coordination of collective behaviours. Social insects like ants, termites or bees make use of different forms of communication, which can be roughly classified in three classes: indirect (stigmergic) communication, direct interaction and direct communication. The use of stigmergic communication is predominant in social insects (e.g., the pheromone trails in ants), but also direct interactions (e.g., antennation in ants) and direct communication can be observed (e.g., the waggle dance of honey bee workers). Direct communication may be beneficial when a fast reaction is expected, as for instance, when a danger is detected and countermeasures must be taken. This is the case of hole avoidance, the task studied in this paper: a group of self-assembled robots – called swarm-bot – coordinately explores an arena containing holes, avoiding to fall into them. In particular, we study the use of direct communication in order to achieve a reaction to the detection of a hole faster than with the sole use of direct interactions through physical links. We rely on artificial evolution for the synthesis of neural network controllers, showing that evolving behaviours that make use of direct communication is more effective than exploiting direct interactions only. Karl von Frisch won a Nobel prize for discovering that when honeybee foragers return to the hive after discovering a new food source, they perform a ‘waggle dance’ conveying coded information about the range and bearing of the food. He hypothesized that ‘recruits’ attending the dance read the code, and use the information to get to the food. Sceptics suggested that the watching bees simply picked up food odours from the dancer and then searched for the food by smell. Though most biologists are inclined to von Frisch's view of the dance as a source of information, the quantitative description of how the ‘code’ is translated into a flightplan has been lacking. Now with the advent of a radar tracking system capable of following the flight paths of individual recruits, show that the bees not only read the dance, but allow for wind drift on their way to the target. An important characteristic of a robot swarm that must operate in the real world is the ability to cope with changeable environments by exhibiting behavioural plasticity at the collective level. For example, a swarm of foraging robots should be able to repeatedly reorganise in order to exploit resource deposits that appear intermittently in different locations throughout their environment. In this paper, we report on simulation experiments with homogeneous foraging robot teams and show that analysing swarm behaviour in terms of information flow can help us to identify whether a particular behavioural strategy is likely to exhibit useful swarm plasticity in response to dynamic environments. While it is beneficial to maximise the rate at which robots share information when they make collective decisions in a static environment, plastic swarm behaviour in changeable environments requires regulated information transfer in order to achieve a balance between the exploitation of existing information and exploration leading to acquisition of new information. We give examples of how information flow analysis can help designers to decide on robot control strategies with relevance to a number of applications explored in the swarm robotics literature.