Abstract:
This research solves a major problem in multi-robot systems that how robots can work together and make consistent decisions even when they don’t share the same information, all while minimizing the need for constant communication. The algorithms developed allow robots to figure out their own actions, predict what others might do, and understand how others will view their decisions. Communication only happens when there’s a disagreement, helping save bandwidth and reduce delays. A key part of this solution is the VERIFYAC algorithm, which helps robots make coordinated decisions by focusing on the most important information and sharing only what’s necessary. To make it even more efficient, an improvement was added that prioritizes the biggest problems first, reducing communication even further. This approach is shown to work in situations like search-and-rescue missions, where robots need to cooperate effectively despite unreliable communication. The method ensures robots can work safely, efficiently, and reliably in critical applications such as disaster response, self-driving cars, and environmental monitoring.
