This research presents a trajectory planning approach for robotic assembly of lightweight structures for COVID-19 healthcare facilities. The prefabricated building components of COVID-19 healthcare facilities have nonnegligible volume, where the crux of the scientific question lies in how to incorporate geometry-based collision checks in trajectory planning. This research developed an algorithm that refines the RRT* (Rapidly-exploring Random Tree-Star) algorithm to enable the detour of a planned trajectory based on the geometry of prefabricated components to prevent collisions. Testing of the approach reveals that it has satisfactory collision-avoiding and trajectory-smoothing performance, and is time- and labour-saving compared with the traditional human method. The satisfactory results highlight the practical implication of this research, where robots can replace human labour and contribute to the mitigation of COVID-19 spread on construction sites. The subsequent research will investigate the use of a collaborative robot to screw bolt connections after the components are assembled at locations.

本研究提出了一种轨迹规划方法，用于为 COVID-19 医疗机构装配轻型结构的机器人。COVID-19 医疗设施的预制建筑组件体积不可忽视，科学问题的症结在于如何将基于几何的碰撞检查纳入轨迹规划。这项研究开发了一种算法，该算法改进了 RRT*（快速探索随机树星）算法，使基于预制组件几何形状的计划轨迹能够绕行以防止碰撞。对该方法的测试表明，该方法具有令人满意的避碰和轨迹平滑性能，并且与传统的人工方法相比更省时省力。令人满意的结果凸显了本研究的实际意义，机器人可以取代人工并有助于缓解 COVID-19 在建筑工地上的传播。随后的研究将调查在部件组装到位后使用协作机器人拧紧螺栓连接。