Abstract
Swarm-bots consist of a collection of mobile robots able to self-assemble and to self-organize so to
solve problems that could not be solved by a single robot. They combines the power of swarm
intelligence and the flexibility of self-reconfiguration as aggregate swarm-bots have the ability to
dynamically change their structure to match environmental variability.
SWARM-BOTS, a project funded by the Future and Emerging Technologies program of the
European Community (project IST-2000-31010), focuses on the design and the implementation of
self-organising and self-assembling biologically-inspired robots. The project benefits from the joint
activity of four European research institutes: the Artificial Intelligence Laboratory of the Université
Libre de Bruxelles (IRIDIA); Dalle Molle Institute of Artificial Intelligence Studies of Lugano
(IDSIA); the Autonomous Systems Laboratory of the Swiss Federal Institute of Technology (ASLEPFL),
and the Institute of Cognitive Sciences and Technology of the Italian National Research
Council (ISTC-CNR).
A swarm-bot is an aggregate of s-bots (mobile robots able to self-assemble by
connecting/disconnecting from each other) capable of performing exploration, navigation and
transportation of heavy objects on rough terrains in situations in which a single s-bot has major
problems at achieving the task alone (see Figure 1 and 2). Each s-bot has simple sensors and
motors, limited computational capabilities, and physical links that allow it to connect to other sbots.
The swarm-bot should move as a whole and reconfigure along the way when needed. For
example, it might have to adopt a different shape in order to go through a narrow passage or
overcome an obstacle. Finally, the aggregate should form as a result of self-organizing rules
followed by each individual s-bot rather than via a global template. Thus swarm-bots combine the
power of swarm intelligence, as they are based on the emergent collective intelligence of groups of
robots, and the flexibility of self-reconfiguration as aggregate swarm-bots might have the ability to
dynamically change their structure to match environmental variability.
At the present stage, we developed the hardware design (the first hardware prototypes will be ready
in the next few weeks). As shown in the Figure, each s-bot has a cylindrical body with a diameter of
116 mm and consists of a mobile base provided with two differential drive mechanisms controlling
tracks and wheels, and a main body provided with two grippers that allow an s-bot to assemble with
other s-bots or to grasp objects. The first gripper is supported by a mobile structure that can rotate
around an horizontal axis and the second gripper is supported by a motorized arm that allows large
movements through the vertical and horizontal axis. The main body rotates with respect to the base
supporting the tracks. From the sensory point of view, each s-bot is provided with proximity
sensors, light sensors, accelerometers, humidity sensors, sound sensors, an omni-directional color
camera, light barrier sensors (on the grippers), force sensors etc.
To develop the control systems of a swarm-bot we are following two different but complementary
research directions. The former consists in building control systems by mimicking the
characteristics of biological systems such as social insects. The latter consists in building control
systems that are only loosely inspired by what we know about real organisms and develop their
ability through a self-organization process based on artificial evolution. At the present stage, by
following the first approach, we were able to develop, for example, the control systems of a group
of simple LEGOTM robots that are able to aggregate into chain formations. By following the latter
approach, we were able to develop simulated s-bots able to display coordinated movements,
collective obstacle avoidance, and object pushing/pulling (see Figure 3 and
Potential application of this novel type of robot are, for instance, semi-automatic space exploration,
search for rescue or underwater exploration.

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