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 However, communication and utilization of potentially outdated information is also a concern.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.
Conversely, explicit communication is the act of communicating directly with other entities @cite_22 @cite_14 . This can be done in many ways. In the case of bees, the medium is a form of dance, known as the waggle dance @cite_26 @cite_19 . This dance may need to be repeated if the bees fail to find the location encoded within it. Using this method, robots have danced in order to communicate source locations to the rest of the swarm @cite_20 .
@cite_14 @cite_26 @cite_22 @cite_19 @cite_20
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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. We investigate avenues for the exchange of information (explicit communication) among deaf and dumb mobile robots scattered in the plane. We introduce the use of movement-signals (analogously to flight signals and bees waggle) as a mean to transfer messages, enabling the use of distributed algorithms among robots. We propose one-to-one deterministic movement protocols that implement explicit communication among asynchronous robots. We first show how the movements of robots can provide implicit acknowledgment in asynchronous systems. We use this result to design one-to-one communication among a pair of robots. Then, we propose two one-to-one communication protocols for any system of n *** 2 robots. The former works for robots equipped with observable IDs that agree on a common direction (sense of direction). The latter enables one-to-one communication assuming robots devoid of any observable IDs or sense of direction. All three protocols (for either two or any number of robots) assume that no robot remains inactive forever. However, they cannot avoid that the robots move either away or closer of each others, by the way requiring robots with an infinite visibility. In this paper, we also present how to overcome these two disadvantages. These protocols enable the use of distributing algorithms based on message exchanges among swarms of Stigmergic robots. They also allow robots to be equipped with the means of communication to tolerate faults in their communication devices. In social insects, both self-organisation and communication play a crucial role for the accomplishment of many tasks at a collective level. Communication is performed with different modalities, which can be roughly classified into three classes: indirect (stigmergic) communication, direct interactions and direct communication. The use of stigmergic communication is predominant in social insects (e.g. the pheromone trails in ants), where, however, direct interactions (e.g. antennation in ants) and direct communication (e.g. the waggle dance in honey bees) can also be observed. Taking inspiration from insect societies, we present an experimental study of self-organising behaviours for a group of robots, which exploit communication to coordinate their activities. In particular, the robots are placed in an arena presenting holes and open borders, which they should avoid while moving coordinately. Artificial evolution is responsible for the synthesis in a simulated environment of the robot’s neural controllers, which are subsequently tested on physical robots. We study different communication strategies among the robots: no direct communication, handcrafted signalling and a completely evolved approach. We show that the latter is the most efficient, suggesting that artificial evolution can produce behaviours that are more adaptive than those obtained with conventional design methodologies. Moreover, we show that the evolved controllers produce a self-organising system that is robust enough to be tested on physical robots, notwithstanding the huge gap between simulation and reality. Human communication involves a number of nonverbal cues that are seemingly unintentional, unconscious, and automatic-both in their production and perception-and convey rich information on the emotional state and intentions of an individual. One family of such cues is called "nonverbal leakage." In this paper, we explore whether people can read nonverbal leakage cues-particularly gaze cues-in humanlike robots and make inferences on robots' intentions, and whether the physical design of the robot affects these inferences. We designed a gaze cue for Geminoid-a highly humanlike android-and Robovie-a robot with stylized, abstract humanlike features-that allowed the robots to "leak" information on what they might have in mind. In a controlled laboratory experiment, we asked participants to play a game of guessing with either of the robots and evaluated how the gaze cue affected participants' task performance. We found that the gaze cue did, in fact, lead to better performance, from which we infer that the cue led to attributions of mental states and intentionality. Our results have implications for robot design, particularly for designing expression of intentionality, and for our understanding of how people respond to human social cues when they are enacted by robots.