Aerial drones have great potential to monitor large areas quickly and efficiently. Aquaculture is an industry that requires continuous water quality data to successfully grow and harvest fish. The Hybrid Aerial Underwater Robotic System (HAUCS) is designed to collect water quality data of aquaculture ponds to reduce labor costs for farmers. The routing of drones to cover each fish pond on an aquaculture farm can be reduced to the Vehicle Routing Problem. A dataset is created to simulate the distribution of ponds on a farm and is used to assess the HAUCS Path Planning Algorithm (HPP). Its performance is compared with the Google Linear Optimization Package (GLOP) and a Graph Attention Model (AM) for routing problems. GLOP is the most efficient solver for 50 to 200 ponds at the expense of long run times, while HPP outperforms the other methods in solution quality and run time for instances larger than 200 ponds.
翻译:航空无人机具有快速高效地监测大片面积的巨大潜力。水产养殖业是一个需要持续水质数据才能成功生长和捕捞鱼类的行业。混合水下水下机器人系统(HAUCS)旨在收集水产养殖池水质量数据,以减少农民的劳动力成本。无人机覆盖水产养殖场上每个鱼池的路线可以减少为车辆运行问题。建立一个数据集,模拟农场池塘的分布,并用来评估HAUCS路径规划Algorithm(HPP),其性能与谷歌线性优化成套软件(Google Linear Opitimization Appim)和用于路由问题的图形关注模型(AM)相比。GlogalP是50至200个水池中最高效的解决器,但花费了很长的时间,而HPP在解决方案质量上超过其他方法,运行的时间超过200个池塘。