Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.
The availability of relatively capable and inexpensive hardware components has made it feasible to consider large-scale systems of autonomous aquatic drones for maritime tasks. In this paper, we present the CORATAM and HANCAD projects, which focus on the fundamental challenges related to communication and control in swarms of aquatic drones. We argue for: (i) the adoption of a heterogeneous approach to communication in which a small subset of the drones have long-range communication capabilities while the majority carry only short-range communication hardware, and (ii) the use of decentralized control to facilitate inherent robustness and scalability. A heterogeneous communication system and decentralized control allow for the average drone to be kept relatively simple and therefore inexpensive. To assess the proposed methodology, we are currently building 25 prototype drones from off-the-shelf components. We present the current hardware designs and discuss the results of simulation-based experiments involving swarms of up to 1,000 aquatic drones that successfully patrolled a 20 km-long strip for 24 hours.
Swarm robotics is a promising approach characterized by large numbers of relatively small and inexpensive robots. Since such systems typically rely on decentralized control and local communication, they exhibit a number of interesting and useful properties, namely scalability, robustness to individual faults, and flexibility. In this paper, we detail the design and development process of a swarm robotics platform composed of autonomous surface robots, which was designed in order to study the use of robotic swarms in real-world environments. Our aquatic surface robots where manufactured using digital fabrication techniques, such as 3D printing and CNC milling, and all hardware and software has been made available as open-source, thus allowing third-parties to customize and further improve our platform.
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