Duke University researchers have proposed a new approach for coordinating complex tasks between hundreds of robots while satisfying logic-based rules.
The method, called STyLuS* (large-Scale optimal Temporal Logic Synthesis), bypasses the traditional requirement of building incredibly large graphs of each robot's locations or nodes by producing smaller approximations with a tree structure.
At each step of the process, the algorithm randomly chooses one node from the large graph, adds it to the tree, and rewires the existing paths between tree nodes to find more direct paths from start to finish.
STyLuS* also selects the next node to add based on data about the task at hand, allowing the tree to quickly approximate a good solution to the problem.
The algorithm solves problems exponentially: it answered the challenge of 10 robots searching through a 50-by-50 grid space in about 20 seconds, while state-of-the-art algorithms would take 30 minutes.
From Duke University Pratt School of Engineering
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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA
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