Swarm behaviours can be divided into 4 aggregate categories:
- Spatial organisation
- Navigation
- Decision making
- Miscellaneous
These behaviors allow the movement of the robots in a swarm in the environment in order to spatially organise themselves or objects.
moves the individual robots to congregate spatially in a specific region of the environment. This allows individuals of the swarm to get spatially close to each other for further interaction.
arranges the swarm of robots in a specific shape. A special case is chain formation where robots form a line, typically to establish multi-hop communication between two points.
connects the robots in order to establish structures. They can either be connected physically or virtually through communication links. A special case is morphogenesis where the swarm evolves into a predefined shape.
lets the swarm of robots manipulate spatially distributed objects. Clustering and assembling of objects is essential for construction processes.
These behaviors allow the coordinated movement of a swarm of robots in the environment.
navigates the swarm of robots cooperatively through the environment in order to explore it. It can be used to get a situational overview, search for objects, monitor the environment, or establish a communication network.
moves the swarm of robots in a formation. The formation can have a well-defined shape, e.g., a line, or be arbitrary as in flocking.
by the swarm of robots enables to collectively move objects which are too heavy or too large for individual robots.
allows the robots in the swarm to find their position and orientation relative to each other via establishment of a local coordinate system throughout the swarm.
These behaviors allow the robots in a swarm to take a common choice on a given issue.
allows the individual robots in the swarm to agree on or converge toward a single common choice from several alternatives.
assigns arising tasks dynamically to the individual robots of the swarm. Its goal is to maximize performance of the entire swarm system. If the robots have heterogeneous capabilities, the tasks can be distributed accordingly to further increase the system’s performance.
within the swarm of robots determines deficiencies of individual robots. It allows to determine robots that deviate from the desired behavior of the swarm, e.g., due to hardware failures.
combines the data locally sensed by the robots in the swarm into a big picture. It allows the swarm to make collective decisions in an informed way, e.g., to classify objects reliably, allocate an appropriate fraction of robots to a specific task, or to determine the optimal solution to a global problem.
aligns frequency and phase of oscillators of the robots in the swarm. Thereby, the robots have a common understanding of time which allows them to perform actions synchronously.
allows the robots in the swarm to form groups of desired size. If the size of the swarm exceeds the desired group size, it splits into multiple groups.
There are further behaviors of swarm robots that fit neither of the categories above.
allows the swarm to recover from faults caused by deficiencies of individual robots. The goal is thus to minimize the impact of robot failure on the rest of the swarm to increase its reliability, robustness, and performance.
allows a swarm of robots either to create new robots or replicate the pattern created from many individuals. The goal is to increase the autonomy of the swarm by eliminating the need of a human engineer to create new robots.
allows humans to control the robots in the swarm or receive information from them. The interaction can happen remotely, e.g., through a computer terminal or proximal in a shared environment, e.g., through visual or acoustic clues.
From Paper - Swarm Robotic Behaviors and Current Applications