  In this paper, we present a novel swarm algorithm, swarm synergy, designed
for robots to form communities within a swarm autonomously and anonymously.
These communities, characterized as clusters of robots, emerge without any
(pre-defined or communicated) specific locations. Each robot operates as a
silent agent, having no communication capability, making independent decisions
based on local parameters. The proposed algorithm allows silent robots to
achieve this self-organized swarm behavior using only sensory inputs from the
environment. The robots intend to form a community by sensing the neighbors,
creating synergy in a bounded environment. We further infer the behavior of
swarm synergy to ensure the anonymity/untraceability of both robots and
communities and show the results on dynamicity of various parameters relevant
to swarm communities such as community size, community location, number of
community, no specific agent structure in the community, etc. The results are
further analysed to observe the effect of sensing limitations posed by the
onboard sensor's field of view. Simulations and experiments are performed to
showcase the algorithm's scalability, robustness, and fast convergence.
Compared to the state-of-art with similar objectives, the proposed
communication-free swarm synergy shows comparative time to synergize or form
communities. The proposed algorithm finds applications in studying crowd
dynamics under high-stress scenarios such as fire, attacks, or disasters.
