Selective harvesting by autonomous robots will be a critical enabling technology for future farming. Increases in inflation and shortages of skilled labour are driving factors that can help encourage user acceptability of robotic harvesting. For example, robotic strawberry harvesting requires real-time high-precision fruit localisation, 3D mapping and path planning for 3-D cluster manipulation. Whilst industry and academia have developed multiple strawberry harvesting robots, none have yet achieved human-cost parity. Achieving this goal requires increased picking speed (perception, control and movement), accuracy and the development of low-cost robotic system designs. We propose the edge-server over 5G for Selective Harvesting (E5SH) system, which is an integration of high bandwidth and low latency Fifth Generation (5G) mobile network into a crop harvesting robotic platform, which we view as an enabler for future robotic harvesting systems. We also consider processing scale and speed in conjunction with system environmental and energy costs. A system architecture is presented and evaluated with support from quantitative results from a series of experiments that compare the performance of the system in response to different architecture choices, including image segmentation models, network infrastructure (5G vs WiFi) and messaging protocols such as Message Queuing Telemetry Transport (MQTT) and Transport Control Protocol Robot Operating System (TCPROS). Our results demonstrate that the E5SH system delivers step-change peak processing performance speedup of above 18-fold than a stand-alone embedded computing Nvidia Jetson Xavier NX (NJXN) system.

翻译：自主机器人的选择性收获将成为未来农业的关键使能技术。通货膨胀加剧和熟练劳动力短缺是推动用户接受机器人收获技术的重要因素。以草莓机器人收获为例，该过程需要实时高精度果实定位、三维建图以及针对三维簇状果实的路径规划。尽管工业界和学术界已开发出多款草莓收获机器人，但尚未实现与人工成本的持平。达成此目标需要提升采摘速度（感知、控制与运动）、精度，并开发低成本机器人系统设计方案。本文提出面向选择性收获的5G边缘服务器系统，该系统将高带宽、低延迟的第五代移动通信网络与作物收获机器人平台相集成，我们视其为未来机器人收获系统的关键使能技术。我们同时考量了处理规模、速度与系统环境及能耗成本的协同关系。通过提出系统架构并开展实验量化评估，比较了不同架构选择下的系统性能，包括图像分割模型、网络基础设施（5G对比WiFi）以及消息传输协议（如消息队列遥测传输协议与传输控制协议机器人操作系统）。实验结果表明，相较于独立的嵌入式计算平台英伟达杰森泽维尔NX系统，本系统实现了超过18倍的峰值处理性能加速。