The adoption of multiple robots for collaborative additive manufacturing is rapidly gaining attention in the industry and research community due to their numerous advantages, such as fast and efficient printing of large-scale parts and their suitability for hazardous or extraterrestrial environments. However, to fully harness the potential of multi-robot additive manufacturing systems, several challenges must be addressed from a process planning perspective. These include part decomposition, part/robot placement, trajectory planning, and print scheduling considering various quality, energy efficiency, time, and reachability constraints as well as different robotic team compositions including mobile/stationary robots, aerial mobility/ground mobility, and heterogenous/homogenous teams. This work explores the optimal positioning of part with respect to the 3D printer robots and inversely the 3D printer robots with respect to the part in case of large structures (given that the structure is assumed to be grounded/fixed and not movable) in multi-robot additive manufacturing scenarios. A novel decision-making methodology for the robot placement problem, i.e., optimal positioning of multiple robots around a large-scale structure, based on the energy consumption of the robots during the additive manufacturing process as well as the final dimensional accuracy of the printed structure, is proposed. The decision making is guided by the construction of a 3D spatial energy-quality map around each of the robot's bases based on their kinematics as well as the geometry of the assigned part for additive manufacturing using the proposed energy and quality modules. Additionally, the simulated annealing algorithm is adopted to quickly identify the optimal robot positionings for the collaborative additive manufacturing task. Different case studies demonstrating the effectiveness of the proposed methodology in reducing energy consumption while maintaining the required print quality are presented. Finally, sensitivity analyses are performed to evaluate the impact of various parameters including the robot velocity and acceleration, number of robots, decomposition scenarios, and ratio of the printed geometry with respect to the robot's reach on the energy and quality metrics.

中文翻译：

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多机器人增材制造中最佳机器人放置的三维空间能量质量图构建

采用多个机器人进行协同增材制造由于其众多优点（例如快速高效地打印大型零件以及适用于危险或外星环境）而迅速受到工业界和研究界的关注。然而，为了充分利用多机器人增材制造系统的潜力，必须从工艺规划的角度解决几个挑战。这些包括零件分解、零件/机器人放置、轨迹规划和打印调度，考虑各种质量、能源效率、时间和可达性约束以及不同的机器人团队组成，包括移动/固定机器人、空中移动/地面移动和异构/同质化的团队。这项工作探索了零件相对于 3D 打印机机器人的最佳定位，以及在大型结构的情况下 3D 打印机机器人相对于零件的最佳定位（假设该结构被假设为接地/固定且不可移动）。机器人增材制造场景。一种针对机器人放置问题的新颖决策方法，即根据增材制造过程中机器人的能耗以及打印结构的最终尺寸精度，在大型结构周围优化多个机器人的定位，提出。决策过程是根据每个机器人底座的运动学以及使用建议的能量和质量模块进行增材制造的指定零件的几何形状构建 3D 空间能量质量图来指导的。此外，采用模拟退火算法来快速确定协作增材制造任务的最佳机器人定位。不同的案例研究证明了所提出的方法在降低能耗同时保持所需打印质量方面的有效性。最后，进行敏感性分析以评估各种参数的影响，包括机器人速度和加速度、机器人数量、分解场景以及打印几何形状相对于机器人触及范围的比率对能量和质量指标的影响。