Robot Coverage Path Planning under Uncertainty Using Knowledge Inference and Hedge Algebras
Robot Coverage Path Planning under Uncertainty Using Knowledge Inference and Hedge Algebras is a scholarly work, published in 2018 in ''Machines''. The main subjects of the publication include path, ocular adaptation, motion planning, artificial intelligence, hedge, robot, reinforcement learning, Archaeological plan, machine learning, inference, and computer science. The paper proposes a novel approach to enable autonomous robotic systems to achieve efficient coverage path planning, which combines adaptation with knowledge reasoning techniques and hedge algebras to achieve optimal coverage path planning in multiple decision-making under dynamic operating environments.