Robots with a high level of autonomy are increasingly requested by smart industries. A way to reduce the workers' stress and effort is to optimize the working environment by taking advantage of autonomous collaborative robots. A typical task for Human-Robot Collaboration (HRC) which improves the working setup in an industrial environment is the \textit{"bring me an object please"} where the user asks the collaborator to search for an object while he/she is focused on something else. As often happens, science fiction is ahead of the times, indeed, in the \textit{Iron Man} movie, the robot \textit{Dum-E} helps its creator, \textit{Tony Stark}, to create its famous armours. The ability of the robot to comprehend the semantics of the environment and engage with it is valuable for the human execution of more intricate tasks. In this work, we reproduce this operation to enable a mobile robot with manipulation and grasping capabilities to leverage its geometric and semantic understanding of the environment for the execution of the \textit{Bring Me} action, thereby assisting a worker autonomously. Results are provided to validate the proposed workflow in a simulated environment populated with objects and people. This framework aims to take a step forward in assistive robotics autonomy for industries and domestic environments.

翻译：高度自主的机器人正日益受到智能工业的青睐。通过利用自主协作机器人优化工作环境，可有效减轻工人的压力和负担。在工业环境中改善工作配置的典型人机协作（HRC）任务当属"请帮我拿件物品"场景：用户专注于其他事务时，要求协作机器人搜索目标物体。正如科幻作品常领先于时代，在《钢铁侠》电影中，机器人"Dum-E"协助其创造者"托尼·斯塔克"打造传奇战甲。机器人理解环境语义并与之交互的能力，对人类执行更复杂任务具有重要价值。本研究重现该操作流程，使具备操作与抓取能力的移动机器人能利用其对环境的几何与语义理解执行"拿取"指令，从而自主协助工人工作。在包含物体和人物的仿真环境中进行的验证结果证明该工作流的有效性。本框架旨在推动工业及家庭环境中辅助机器人自主性的进步。