Climate change and resource depletion demand a shift from the dominant linear "take-make-use-dispose" paradigm of construction toward circular, low-waste practices. Material reuse offers a promising pathway by reducing raw material extraction, mitigating waste, and extending the service lifespan of carbon-sequestering materials such as timber. Realizing this potential, however, requires addressing technical and logistical challenges across both design and construction for accommodating heterogeneous, reclaimed material inventories. This paper presents an integrated framework that couples data-driven computational design with feedback-driven adaptive human-robot collaborative (co-robotic) fabrication and assembly to enable the realization of nonstandard structures made from reclaimed timber of varying length and geometries, supplemented with new off-the-shelf timber when necessary. The framework is validated through Timbrelyn, a built case-study installation that demonstrates how timber reuse can inform and enhance architectural expression. This work contributes to the development of integrated design-to-fabrication workflows that advance adaptive, feedback-driven methods to handle inventory constraints and reclaimed material uncertainties, facilitating material reuse in the design and construction of new buildings and structures.

翻译：气候变化和资源枯竭要求建筑业从主流的线性“获取-制造-使用-废弃”范式转向循环、低废料实践。材料再利用通过减少原材料开采、减轻废物产生并延长碳封存材料（如木材）的使用寿命，提供了一条有前景的路径。然而，实现这一潜力需要解决设计和施工中适应异构、回收材料库存的技术和物流挑战。本文提出一个集成框架，将数据驱动的计算设计与反馈驱动的自适应人机协作（共机器人）制造和装配相结合，以实现由不同长度和几何形状的回收木材制成的非标准结构，必要时辅以新的现成木材。该框架通过Timbrelyn案例研究装置进行验证，展示了木材再利用如何启发并增强建筑表达。本文有助于开发集成的设计到制造工作流程，推进自适应、反馈驱动的方法来处理库存限制和回收材料的不确定性，从而促进新建筑和结构设计与施工中的材料再利用。