Navigating The Future: A Systematic Review on the Role of Quantum Computing in Multi-Robot Systems
Abstract
More and more, multi-robot systems (MRS) are being used for hard tasks like industrial automation, surveillance, and autonomous navigation. Nevertheless, these systems have significant computation difficulties especially in path planning, task distribution and coordination. Quantum computing is capable of computing information based on such concepts as superposition and entanglement. This provides an alternative solution to optimization problems that are more efficient than the conventional methods. A systematic review approach based on PRISMA was used. We used pre-set search terms to look for useful papers in databases including Google Scholar, Scopus, IEEE Xplore, and Web of Science. We found peer-reviewed articles that had come out in the last 10 to 15 years based on some rules for which ones to include and which ones to leave out. A total of thirty papers, mainly focusing on algorithms, applications and constraints were included in qualitative synthesis. The review demonstrated that quantum algorithms, such as the search and QAOA algorithms created by Grover, can be helpful in optimizing the problems of MRS. These methods have the benefits of parallelism and speed. Nevertheless, they are used in simulations only due to the limitations of technology, scaling issues, and integration challenges with real-time robotic system.
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Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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