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Research team introduces an agile multi-robot research platform

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Teams of robots have the potential of tackling far more elaborate missions than individual robots, for instance, covering long distances faster, visiting different sites simultaneously, or monitoring larger geographical areas. .
Teams of robots have the potential of tackling far more elaborate missions than individual robots, for instance, covering long distances faster, visiting different sites simultaneously, or monitoring larger geographical areas. Platforms that combine reliable hardware and software for multi-robot applications could help to advance research in this field, facilitating the testing of robot teams in specific real-world settings.
Researchers at the University of Cambridge recently introduced the Cambridge RoboMaster, a promising platform for multi-robot research. This platform, outlined in a paper pre-published on arXiv, includes the design of a fleet of customized Robomaster wheeled robots, along with software to simulate and train the robots on specific tasks.
„Our mission is to develop solutions for collective intelligence in multi-robot and multi-agent systems,“ Amanda Prorok, Principal Investigator, told Tech Xplore. „This research incorporates methods from machine learning, planning, and control, with a wide range of applications, including automated transport, logistics, environmental monitoring, and search and rescue. To validate our research, we needed a robust and capable robotic platform.“
Blumenkamp and his colleagues set out to develop a multi-robot research platform that met a series of requirements, namely state-of-the-art computing power, speed, agility and durability. Ultimately, they decided to use customized versions of DJI RoboMaster S1 robots, small, wheeled robots that were originally designed for high school and university-level competitions.
„This platform provided a solid foundation that we could build upon to meet our specific needs,“ Blumenkamp said. „Over the past three years, we have continued to work on this robotic platform, and we continuously iterated on and improved its capabilities.

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