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Distributed Robotics


Modular Robots Distributed Robotics Networked Robots Animals and Robots Sensor Networks Underwater Robotics 3D Navigation Desktop Robotics

Distributed Algorithms and Systems of Self-organizing Robots

Distributed Learning
Distributed Manipulation
Distributed Coverage Control

Our goal is to study self-organizing systems. A self-organizing
system consists of multiple autonomous components that make local
decisions leading to a global coordinated behavior for the system.
Such systems can organize autonomously in different ways, thus adapting
to task and environment. Local sensing and communication to nearby
neighbors allow the individual units to find their place in the
larger system goal.

Self-organizing robots are well-suited for tasks in hazardous and
remote environments, especially when the environmental model and the
task specifications are uncertain. A collection of simple, modular
robots endowed with self-organizing capabilities can conform to
the shape of the terrain for locomotion by implementing compliant
``water-flow''-like locomotion gaits. They can distribute
themselves to form a sensor network for surveillance and
monitoring. The robots in such a system can also collaborate
to perform sophisticated manipulation tasks. Moreover, a modular
platform could carry a collection of self-reconfiguring modules to a
site. The modules could then grow into a tower, enter the site
through a small opening (such as a window) and reconfigure to survey
the site.

To create autonomous robot systems capable of such applications, a
fundamental goal of this research is to further the science-base for
modular self-organizing systems. This is a considerable challenge,
which we propose to meet by the synergistic integration of the following
new directions of work with our existing work:

1. Designing heterogeneous robot systems with self-organization
capabilities. In the past we designed the Molecule Robot and the
Crystal Robot. Our current focus is to design self-organizing
adaptive mobile trusses that consist of active and passive parts

2. Focus on distributed and generic rather than
architecture-specific algorithms;

3. Focus on heterogeneous rather than homogeneous systems;

4. Focus on automating the development and analysis of the
algorithms used to control these robots.