This paper introduces a wall construction planner for Unmanned Aerial Vehicles (UAVs), which uses a Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic to generate near-time-optimal building plans for even large walls within seconds. This approach addresses one of the most time-consuming and labor-intensive tasks, while also minimizing workers' safety risks. To achieve this, the wall-building problem is modeled as a variant of the Team Orienteering Problem and is formulated as Mixed-Integer Linear Programming (MILP), with added precedence and concurrence constraints that ensure bricks are built in the correct order and without collision between cooperating agents. The GRASP planner is validated in a realistic simulation and demonstrated to find solutions with similar quality as the optimal MILP, but much faster. Moreover, it outperforms all other state-of-the-art planning approaches in the majority of test cases. This paper presents a significant advancement in the field of automated wall construction, demonstrating the potential of UAVs and optimization algorithms in improving the efficiency and safety of construction projects.

翻译：本文介绍了一种适用于无人机（UAV）的墙体施工规划器，该规划器采用贪心随机自适应搜索过程（GRASP）元启发式算法，能够在数秒内为大型墙体生成近乎时间最优的建造方案。该方法解决了建筑行业中最耗时耗力的任务之一，同时最大程度降低了工人的安全风险。为此，我们将墙体建造问题建模为团队定向问题的变体，并表述为混合整数线性规划（MILP），同时增加了前后顺序约束与并发约束，以确保砖块按正确顺序砌筑且协作智能体之间不发生碰撞。通过在逼真仿真环境中验证，该GRASP规划器能够找到与最优MILP质量相近的解，但求解速度显著更快。此外，在大多数测试案例中，其性能优于所有其他现有规划方法。本文在自动化墙体施工领域取得了重大进展，展示了无人机与优化算法在提升施工项目效率与安全性方面的潜力。