用模块化机器人自动完成建筑任务，从指令到执行全程智能适配。
Holistic Construction Automation with Modular Robots: From High-Level Task Specification to Execution
- 基于BIM的动态优化，为每项任务自动生成专用机器人形态。
- 支持多目标优化，可应对实际施工中的校准误差等挑战。
- 适用于建筑自动化领域，尤其适合缺乏专业机器人人员的场景。
现场建筑机器人自动化面临环境变化频繁、机器人专家短缺及机器人与施工流程缺乏标准化衔接的挑战。本文提出一种全流程框架，涵盖施工任务定义、机器人构型优化与任务执行，采用移动式模块化可重构机器人实现。用户可通过图形界面指定并监控机器人行为。与传统一体化方案不同，本框架通过集成建筑信息模型（BIM），为每个任务自动识别定制化的机器人结构。利用模块化组件，可快速调整硬件以满足具体施工需求。区别于以往模块化机器人优化研究，本工作考虑多个竞争性目标，显式建模真实场景转移中的挑战，如校准误差。仿真中验证了钻孔和喷涂任务的机器人优化效果。实验结果表明，该方法能稳健实现机器人自主钻孔作业。
原文摘要 · Abstract (English)
In situ robotic automation in construction is challenging due to constantly changing environments, a shortage of robotic experts, and a lack of standardized frameworks bridging robotics and construction practices. This work proposes a holistic framework for construction task specification, optimization of robot morphology, and mission execution using a mobile modular reconfigurable robot. Users can specify and monitor the desired robot behavior through a graphical interface. In contrast to existing, monolithic solutions, we automatically identify a new task-tailored robot for every task by integrating \acf{bim}. Our framework leverages modular robot components that enable the fast adaption of robot hardware to the specific demands of the construction task. Other than previous works on modular robot optimization, we consider multiple competing objectives, which allow us to explicitly model the challenges of real-world transfer, such as calibration errors. We demonstrate our framework in simulation by optimizing robots for drilling and spray painting. Finally, experimental validation demonstrates that our approach robustly enables the autonomous execution of robotic drilling.
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