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New Principles of Coordination in Large-scale
Micro- and Molecular-Robotic Groups
S. Kornienko, O. Kornienko
Institute of Parallel and Distributed Systems, University of Stuttgart,
Universit¨atsstr. 38, D-70569 Stuttgart, Germany
Abstract—Micro- and molecular-robotic systems act as large-
scale swarms. Capabilities of sensing, communication and infor-
mation processing are very limited on these scales. This short
position paper describes a swarm-based minimalistic approach,
which can be applied for coordinating collective behavior in such
systems.
I. INTRODUCTION
Micro-robots and currently molecular-robotics [2] become
important and extremely challenging branch of modern robotic
research. The domain of micro- and molecular-robotic appli-
cations, such as biotechnologies, micro-systems construction,
molecular engineering, and ﬁnally nanotechnologies, repre-
sents a huge economic, social and technological potential
with a great impact on everyday human life [1]. Due to a
large number of micro-objects, usually they are of hundred
thousands, there is a need of such robotic systems, which
can provide an autonomous and half-autonomous handling
of many small objects. The main focus lies on a high-
parallelization of handling processes performed by collectively
working robots and involves different plan-generating [19] and
planning [16] approaches.
Micro-robots and especially molecular systems, due to
a small size, are very limited in actuation, sensing and
communication [22]. However working in a collective way
requires coordination of robotic behavior. The technological,
size-dependent and functional restrictions hinder applications
of approaches known in a larger mini- and ”normal-size”
robotics. As demonstrated by a few current micro-robotic
projects (robot size 2 × 2 × 2mm)
[3], we need to ﬁnd a
new principles of coordination even in the micro-robotic group
consisting of 1000 robots.
An approach, which can be successfully applied to limited
robotic systems, is based on the low-level properties of optical
perception [21], in particular IR light [14], as well as on
involvement of such processes into e.g. collective decision
making [13] or cognitive processes [15]. More generally,
different nonlinear processes and models [24] can be used for
such purposes. Further in Sec. II we provide an example of
typical problems in limited micro-systems such as collective
information processing and in Sec. III brieﬂy discuss a mech-
anism for solution of this problem.
IARP - IEEE/RAS - EURON Joint Workshop on MICRO & NANO
ROBOTICS, Paris, 23 - 24 October, 2006. This is a post-proceeding version
of this work.
II. CHALLENGE OF COLLECTIVE INFORMATION
PROCESSING
The motivating experiment originated from the swarm re-
search around the ”Jasmine” robot [20]. We use this platform
for testing different bio-inspired approaches, developing algo-
rithms of controllable-emergent [18] collective behavior based
on limited sensing and communication capabilities. This robot
measures 26 × 26 × 20mm (30 × 30 × 20mm in the latest
version), with the number of robots between 50 and 130 in
different experiments [26].
This point of this experiment is related to information
transfer in robotic groups [17]. Information about state of
environment, coordination and decision making processes are
transferred via RF communication globally in the ﬁeld or
service type of robotics. Such a circulation of information is
necessary for keeping all robots aware about environment and
about individual robot’s intensions. This represents a basis for
global coordination mechanisms. Mini- and micro- robotics
uses primarily only local communication. These are e.g. opti-
cal, electromagnetic or even chemical mechanisms. The global
information transfer, and thus coordination mechanisms, can
be produced in this case only by a mechanism that propagates
messages through multiple robot-robot connections. Parame-
ters of a global circulation of information (such as a global
propagation speed or global propagation time) depend on
characteristics of local communication.
Fig. 1.
Global feedback connectivity in experiments with the coop-
erative actuation. Robots, equipped with color sensors are marked
by circles. Thin arrow points to global propagation of messages,
thick arrow points to feedback messages. Behinds are robots that
do not have any connections to the rest of the robots - this cluster is
disconnected from the swarm.
arXiv:1109.3765v1  [cs.RO]  17 Sep 2011
2
Example of such an information transfer can be given by ex-
periments with collective actuation that requires coordination
between robots equipped with color sensors [28], as shown
in Fig. 1. All these robots use local IR-based communication.
In this experiment, the robots-scout, equipped with the color
sensor, found the blue object. It sends a request to the swarm
and asks about a support – it looks for robots with a speciﬁc
functionality (in this case also equipped with the color sensor).
The behavior of robot-scout (and also the swarm) depends on
the feedback signals of other robots with color sensors: when
there are no such robots available, scout will look further;
when at least two other robots give the feedback, the scout
will wait them. This experiment is typical for heterogeneous
systems and can be extended towards larger or smaller scales
and different sensing and actuating capabilities.
The mechanism of the feedback signals and correspond-
ing collective decision making process, which is trivial for
”large” robots with global RF-communication, represents a
challenge for micro-robots. The robots should know when
to stop sending, know the recipience or routing informa-
tion for continuously changing situation in the swarm. Not
only communication, but also limited computational resources
make coordination extremely hard in micro-systems. Complex
symbolic negotiation and coordination strategies known in
different communities [27] can hardly be applied for such
micro-agents.
III. PROPOSED MECHANISMS
The idea is to involve in the coordination and negotiation
process low-complex numerical mechanisms [13], which do
not require global communication channels as well as on-board
computational devices. The required local computation can be
performed directly by hardware (an analog way, e.g. FPAA
or analog ASIC) and can be implemented even on molecular
level [2]. The desired collective behavior of these systems
can be achieved by applying the principle of artiﬁcial self-
organization.
docking stations
buffered area
buffered area
working area
working area
waiting robots
waiting robots
Fig. 2.
Collective energy foraging in a swarm of 50 micro-robots
”Jasmine”. Shown are different roles of robots that are regulated
through the low-complex coordination mechanism.
We implemented such mechanisms for the collective energy
foraging in the group of 50 micro-robots ”Jasmine”, shown
in Fig. 2. Each robot has an individual energy homeostasis.
When robot is ”hungry”, it breaks a current activity and starts
looking for the docking station. However, when all robots do
it in a non-coordinated way, many robots can energetically
die due to ”bottle necks” at the docking station. The imple-
mented mechanism of low-complex collective decision making
provides a coordination mechanism based on the collective
power consumption in the swarm. It prevents such situations
when many robots simultaneously look for the docking station
and maintains the collective energy level of all robots in the
optimal way. Here we do not use global information transfer
or complex local computations.
IV. POST-PROCEEDING COMMENTS
The experiments with collective energy foraging and corre-
sponding bio-inspired and collective decision approaches are
published in [5] and [7]. Issues on artiﬁcial and adaptive [9]
self-organization are explained in [4], on heterogeneity –
in [6] and [11] and morphology – in [8] and [23]. Topics
of adaptability in minimalistic swarms are addressed in [25],
[10], [12] and [9].
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