摘要
在安全监控领域,人工智能技术的引入极大地提升了监控系统的效率和准确性,为及时识别到机器人执行任务时的异常情况,降低异常情况的处理响应时间,保障应急处理机器人误操作的效率,设计人工智能分析视频图像数据的机器人远程监测系统。通过视频数据采集模块实时采集机器人视频图像数据,经由远程通信模块向人工智能分析模块传输此类视频图像数据;运用FCN模型提取机器人视频图像中的机器人位置、速度及轨迹特征向量,输入到高斯分类器内,实现机器人各视频帧的分类,完成机器人远程监测。结果显示,该系统可获取到机器人作业中的位置、速度及轨迹特征信息,并监测到机器人作业中的异常状态,同时,整个监测过程中的视频数据远程通信与分类筛选阶段均具有较高的响应时效。
In the field of safety monitoring,the introduction of artificial intelligence technology has greatly improved the efficiency and accuracy of the monitoring system.In order to identify the abnormal situation when the robot performs the task in time,reduce the response time of the abnormal situation and ensure the efficiency of emergency handling of robot misoperation,a robot remote monitoring system based on artificial intelligence analysis of video image data is designed.Collecting robot video image data in real time through a video data acquisition module,and transmitting the video image data to an artificial intelligence analysis module through a remote communication module;The FCN model is used to extract robot position,velocity and trajectory feature vectors from robot video images,and input them into Gaussian classifier to realize the classification of robot video frames and complete robot remote monitoring.The results show that the system can obtain the position,speed and trajectory characteristic information of robot operation,and monitor the abnormal state of robot operation.At the same time,the video data remote communication and classification and screening stages in the whole monitoring process have high response time.
作者
林瑜
LIN Yu(BeiJing Institute Of Economics And Management,BeiJing 100102,China)
出处
《自动化与仪器仪表》
2025年第7期155-159,共5页
Automation & Instrumentation
关键词
人工智能
视频图像数据
远程监测
全卷积网络
高斯分类器
artificial intelligence
video image data
remote monitoring
full convolution network
gaussian classifier
