摘要 : Collaboration among a group of robots with heterogeneous capabilities is an important research problem that enables to combine different robot functionalities, and thus, conducts complex tasks that may be difficult to achieve by a... 展开 Collaboration among a group of robots with heterogeneous capabilities is an important research problem that enables to combine different robot functionalities, and thus, conducts complex tasks that may be difficult to achieve by a single robot with limited resources. In this article, we propose a new distributed task allocation framework based on the capability matching of heterogeneous robots. The framework is composed of an ontological dynamic knowledge graph model and a hardware control scheme to model the capability and optimize resource utilization for collaborative tasks. We introduce an intuitive hardware control scheme based on a dynamic knowledge graph that resolves possible conflicts between the hardware control of different types of robots. Action sequences are produced by a task and motion planning algorithm to collaboratively perform the assigned task. The performance of the proposed methodology is evaluated by both simulations and hardware experiments. 收起