Towards Designing Index-free : Formation Control
Pena Queralta, Jorge (2018-10-01)
Towards Designing Index-free : Formation Control
Pena Queralta, Jorge
(01.10.2018)
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Turun yliopisto
Tiivistelmä
An agent must be aware of its location and surroundings within a formation. The
awareness can be managed in a centralized or decentralized manner. We focus on a
distributed approach due to its scalability, lower hardware requirements and inspired
by swarms of animals in nature that are able to perform complex actions without a
leader or external input.
In the decentralized approach, an agent usually communicates with other agents
to make decisions of its objective position within the multi-agent system, in order
to achieve consensus. This reserves computational and communication resources.
To reduce the use of resources, we introduce a formation control algorithm with
low sensing and a priori information requirements that requires no communication
between agents.
Our algorithm needs only local coordinate systems with a common orientation and
global a priori information of the formation configuration. It is able to produce
almost-arbitrary formation configurations for multi-agent systems. We show examples
of non-trivial formation shapes that can be achieved with an index-free
approach and based only on local position measurements referenced in individual
oriented coordinate systems. Both the position assignment and movement path are
self-calculated by the individual agents without communication with their neighbors
and based only on position measurements.
In the last chapter of this document, we introduce a vision-based algorithm that
could be implemented in drones or over robots to have a reliable tool for measuring
distance and bearing to other near robots. These measurements can then be used
in the formation control algorithm in order to achieve different formation configurations.
We have developed a vision-based algorithm that uses on-board cameras and
2 LED markers on each of the agents. We have tested this algorithm for detection
of LED markers in environments with different light conditions and distances from
20 cm to 6 m, with satisfactory results.
awareness can be managed in a centralized or decentralized manner. We focus on a
distributed approach due to its scalability, lower hardware requirements and inspired
by swarms of animals in nature that are able to perform complex actions without a
leader or external input.
In the decentralized approach, an agent usually communicates with other agents
to make decisions of its objective position within the multi-agent system, in order
to achieve consensus. This reserves computational and communication resources.
To reduce the use of resources, we introduce a formation control algorithm with
low sensing and a priori information requirements that requires no communication
between agents.
Our algorithm needs only local coordinate systems with a common orientation and
global a priori information of the formation configuration. It is able to produce
almost-arbitrary formation configurations for multi-agent systems. We show examples
of non-trivial formation shapes that can be achieved with an index-free
approach and based only on local position measurements referenced in individual
oriented coordinate systems. Both the position assignment and movement path are
self-calculated by the individual agents without communication with their neighbors
and based only on position measurements.
In the last chapter of this document, we introduce a vision-based algorithm that
could be implemented in drones or over robots to have a reliable tool for measuring
distance and bearing to other near robots. These measurements can then be used
in the formation control algorithm in order to achieve different formation configurations.
We have developed a vision-based algorithm that uses on-board cameras and
2 LED markers on each of the agents. We have tested this algorithm for detection
of LED markers in environments with different light conditions and distances from
20 cm to 6 m, with satisfactory results.