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As multiple and heterogenous unmanned vehicle systems continue to play an increasingly important role in addressing complex missions in the real world, the need for effective cooperation among unmanned vehicles becomes paramount. The concept of autonomous cooperation, wherein unmanned vehicles cooperate without human intervention or human control, offers promising avenues for enhancing the efficiency and adaptability of intelligence of multiple-heterogeneous unmanned vehicle systems. Despite the growing interests in this domain, as far as the authors are concerned, there exists a notable lack of comprehensive literature on defining explicit concept and classifying levels of autonomous cooperation of multiple-heterogeneous unmanned vehicle systems. In this aspect, this article aims to define the explicit concept of autonomous cooperation of multiple-heterogeneous unmanned vehicle systems. Furthermore, we provide a novel criterion to assess the technical maturity of the developed unmanned vehicle systems by classifying the autonomous cooperative levels of multiple-heterogeneous unmanned vehicle systems.

This paper explores the conditions for determining fixed nodes in structured networks, specifically focusing on directed acyclic graphs (DAGs). We introduce several necessary and sufficient conditions for determining fixed nodes in $p$-layered DAGs. This is accomplished by defining the problem of maximum disjoint stems, based on the observation that all DAGs can be represented as hierarchical structures with a unique label for each layer. For structured networks, we discuss the importance of fixed nodes by considering their controllability against the variations of network parameters. Moreover, we present an efficient algorithm that simultaneously performs labeling and fixed node search for $p$-layered DAGs with an analysis of its time complexity. The results presented in this paper have implications for the analysis of controllability at the individual node level in structured networks.

Within the context of structured networks, this paper introduces the concept of the Fixed Strongly Structurally Controllable Subspace (FSSCS), enabling a comprehensive characterization of controllable subspaces. From a graph-theoretical viewpoint, the paper defines Fixed Strongly Structurally Controllable (FSSC) nodes based on the FSSCS concept and establishes the necessary and sufficient conditions for their identification. This paper proposes a method for determining the exact dimension of the Strongly Structurally Controllable Subspace (SSCS) in hierarchical directed acyclic graphs, employing a blend of graph-theoretical approaches and controllability matrix analyses. This approach not only facilitates the identification of FSSC nodes but also enhances our understanding of the robustness of node controllability against variations in network parameters within structured networks, marking a significant advancement in the field of strong structural controllability of individual nodes., Comment: The proofs of Lemma 1 and Theorem 3 have errors