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[目的]针对红花采摘机器人在复杂农田环境中面临的实时感知与控制挑战，特别是多源异构传感器数据处理和对环境变化的快速响应问题，设计一种基于ROS和Qt的多线程并行控制系统。[方法]数据处理引入生产者-消费者模型，实现多源异构传感器数据的实时并行处理，提高系统数据处理效率和鲁棒性，并在新疆吉木萨尔县红旗农场红花田现场试验。[结果]多线程架构在复杂场景中显著优化资源利用率，减少端到端延迟约19.3%～25%。通过任务分解与并行处理，多线程配置在高负载条件下将CPU使用率从单线程的90%降低至75%～80%，并显著平滑内存曲线，提升系统稳定性。[结论]该项目与新疆35家农户、合作社签订技术服务合作协议，对推动红花采摘机械化发展具有重要的理论和实践意义。
Abstract：[Objective]The paper addresses the challenges of real-time perception and control faced by safflower harvesting robots in complex farmland environments, particularly focusing on multi-source heterogeneous sensor data processing and rapid response to environmental changes. [Methods]A multithreaded parallel control system based on ROS and Qt is designed to tackle these issues.The data processing utilizes a producer-consumer model to achieve real-time parallel processing of multi-source heterogeneous sensor data, enhancing the efficiency and robustness of the system. Field experiments were conducted in a safflower field at Hongqi Farm,Jimusar County, Xinjiang. [Results]The results showed that the multithreaded architecture significantly optimized resource utilization and reduced end-to-end latency by approximately 19.3% to 25% in complex scenarios. By task decomposition and parallel processing, the multithreaded configuration reduced CPU usage from 90%(in single-threaded mode) to 75%–80% under high load conditions and significantly smoothed the memory usage curve, improving system stability. The project has signed technical service cooperation agreements with 35 farmers and cooperatives in Xinjiang. [Conclusion]The research findings have significant theoretical and practical value for promoting the mechanization of safflower harvesting.
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基本信息:
DOI：
中图分类号:TP242;S225
引用信息:
[1]郭辉,王翔,武天伦等.基于ROS-QT的红花采摘机器人多线程传感器数据预处理系统[J].沈阳农业大学学报,2025,56(01):117-127.
基金信息:
新疆维吾尔自治区自然科学基金项目(2022D01A117)