In order to improve the task execution capability of home service robot, and to cope with the problem that purely physical robot platforms cannot sense the environment and make decisions online, a method for building digital twin system for home service robot based on motion simulation is proposed. A reliable mapping of the home service robot and its working environment from physical space to digital space is achieved in three dimensions: geometric, physical and functional. In this system, a digital space-oriented URDF file parser is designed and implemented for the automatic construction of the robot geometric model. Next, the physical model is constructed from the kinematic equations of the robot and an improved particle swarm optimization algorithm is proposed for the inverse kinematic solution. In addition, to adapt to the home environment, functional attributes are used to describe household objects, thus improving the semantic description of the digital space for the real home environment. Finally, through geometric model consistency verification, physical model validity verification and virtual-reality consistency verification, it shows that the digital twin system designed in this paper can construct the robot geometric model accurately and completely, complete the operation of household objects successfully, and the digital twin system is effective and practical.

翻译：为提高家用服务机器人的任务执行能力，并解决纯物理机器人平台无法在线感知环境并做出决策的问题，提出了一种基于运动仿真的家用服务机器人数字孪生系统构建方法。该方法从几何、物理和功能三个维度，实现了家用服务机器人及其工作环境从物理空间到数字空间的可靠映射。在该系统中，设计并实现了一种面向数字空间的URDF文件解析器，用于机器人几何模型的自动构建。接着，依据机器人运动学方程构建物理模型，并提出一种改进的粒子群优化算法用于逆运动学求解。此外，为适应家庭环境，采用功能属性描述家居物体，从而提升了数字空间对真实家庭环境的语义描述能力。最后，通过几何模型一致性验证、物理模型有效性验证以及虚实一致性验证，表明本文设计的数字孪生系统能够准确、完整地构建机器人几何模型，成功完成家居物体的操作任务，且该数字孪生系统有效且实用。