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Collective Movement of Mobile Robots

Collective movement of mobile robots is the problem of how to control a group of robots making them move as a group, in a cohesive way, towards a common direction. Collective movement serves not only to move a group of robots from one point to another, but to perform more complex tasks such as using the group of robots as a moving sensor array, collective mapping and searching tasks. In this page some information and videos about the research on this topic are presented grouped in the following subprojects:

A Framework for the Collective Movement of Mobile Robots Based on Distributed Decisions

A novel framework for the control of collective movement of mobile robots is presented and analyzed in this article. It allows a group of robots to move as a unique entity performing the following functions: obstacle avoidance at group level, speed control and modification of the inter-robot distance. Its basic controller is distributed among the robots, allowing them to move in the desired common direction and maintain a desired inter-robot distance.The framework is composed of different modules that modify the behavior of the group allowing different functions. Most are based on consensus algorithms that allow the robots to agree on different parameters, that consider which robot has more relevant information. New modules can be easily designed and incorporated to the framework in order to augment its capabilities. It can be easily implemented on any mobile robot capable of measuring the relative positions of neighboring robots and communicating with them. It has been successfully tested using 8 real robots and in simulation with up to 40 robots, demonstrating experimentally its scalability with an increasing number of robots.

Videos

Basic Movement

Obstacle Avoidance

Split and Rejoin

Inter-robo distance control (3x speed)

Distributed orientation agreement

Related Articles

I. Navarro, Collective Movement in Robotic Swarms, Ph.D. Thesis, UPM, Madrid, Spain, 2010. (Under request)

I. Navarro, F. Matía, A Framework for the Collective Movement of Mobile Robots Based on Distributed Decisions, Robotics and Autonomous Systems, Volume 59, Issue 10, October 2011, Pages 685-697. DOI: 10.1016/j.robot.2011.05.001. [pdf]

I. Navarro, F. Matía, Distributed orientation agreement in a group of robots, Autonomous Robots, Volume 33, Number 4, 2012, Pages 445-465. DOI:10.1007/s10514-012-9300-5. [Link]

A Plume Tracking Algorithm based on Crosswind Formations

We introduce a plume tracking algorithm based on robot formations. The algorithm is inherently designed for multi-robot systems, and requires at least two robots to collaborate. The robots try to keep themselves centered around the plume while moving upwind towards the source, and share their odor concentration and wind direction measurements with each other. In addition, robots know the rela- tive poses of other team members. Systematic experiments with up to 5 real robots in a wind tunnel show that the robots achieve close-to-optimal performance in our scenario, and by far outperform previous approaches. The performance gain is at- tributed to the fact that robots continuously share information about the plume (odor concentration, wind direction) without spatially competing for acquiring it.

Video

Related Article

T. Lochmatter, E. Aydin, I. Navarro and A. Martinoli, A Plume Tracking Algorithm based on Crosswind Formations, in International Symposium on Distributed Autonomous Robotic Systems, Lausanne, Switzerland, 2010. [pdf]

An approach to flocking of robots using minimal local sensing and common orientation

A new algorithm for the control of robot flocking is presented. Flocks of mobile robots are created by the use of local control rules in a fully distributed way, using just local information from simple infra-red sensors and global heading information on each robot. Experiments were done to test the al- gorithm, yielding results in which robots behaved as expected, moving at a rea- sonable velocity and in a cohesive way. Up to seven robots were used in real experiments and up to fifty in simulation.

Video

Related Article

I. Navarro, A. Gutiérrez, F. Matía, and F. Monasterio-Huelin, An approach to flocking of robots using minimal local sensing and common orientation, in Hybrid Artificial Intelligent Systems: 3th International Workshop, HAIS 2008, ser. Lecture Notes in Artificial Intelligence (LNAI), E. Corchado, A. Abraham, and W. Pedrycz, Eds. Berlin, Germany: Springer-Verlag, 2008, vol. 5271, pp. 616-624. ISBN: 978-3-540-87655-7. [pdf]

A Distributed Scalable Approach to Formation Control in Multi-robot Systems

A new algorithm for the control of formations of mobile robots is presented. Formations with a triangular lattice structure are created using distributed control rules, using only local information on each robot. The overall direction of movement of the formation is not pre-established but rather results from local interactions, giving all the robots a common, self-organized heading. Experiments were done to test the algorithm, yielding results in which robots behaved as expected, moving at a reasonable speed and maintaining the desired distances among themselves. Up to seven robots were used in real experiments and up to forty in simulation.

Videos

Related Article

I. Navarro, J. Pugh, A. Martinoli, and F. Matía, Distributed Autonomous Robotic Systems 8. Springer Berlin Heidelberg, 2009, ch. A Distributed Scalable Approach to Formation Control in Multi-robot Systems, pp. 203-214.ISBN: 978-3-642-00643-2. [pdf]