Intelligent agents gather information and perceive semantics within the
environments before taking on given tasks. The agents store the collected
information in the form of environment models that compactly represent the
surrounding environments. The agents, however, can only conduct limited tasks
without an efficient and effective environment model. Thus, such an environment
model takes a crucial role for the autonomy systems of intelligent agents. We
claim the following characteristics for a versatile environment model:
accuracy, applicability, usability, and scalability. Although a number of
researchers have attempted to develop such models that represent environments
precisely to a certain degree, they lack broad applicability, intuitive
usability, and satisfactory scalability. To tackle these limitations, we
propose 3-D scene graph as an environment model and the 3-D scene graph
construction framework. The concise and widely used graph structure readily
guarantees usability as well as scalability for 3-D scene graph. We demonstrate
the accuracy and applicability of the 3-D scene graph by exhibiting the
deployment of the 3-D scene graph in practical applications. Moreover, we
verify the performance of the proposed 3-D scene graph and the framework by
conducting a series of comprehensive experiments under various conditions.

提出了一种用于智能代理系统的多功能环境建模方法 ——3D 场景图模型，其具有广泛的适用性、直观的易用性和满意的可扩展性，并通过实验验证了该方法的准确性和适用性。