基于Python的物流机器人路径规划与障碍识别的研究 毕业论文+源码
摘要
智能机器人的发展已经渗透到人们日常生活的各方各面，日益在人们日常生活中发挥着重要的作用，并且智能机器人跟踪技术是机器人研究领域的一个重要研究方向。云计算正不断应用到各种场景，传统机器人的计算存储等能力受限于其板载设备，将云计算与机器人结合用于提升机器人能力是机器人未来发展的趋势之一。
本毕业设计课题基于Python实现机器人目标路径规划，需要将障碍识别迁移到云服务器，云服务实时的通过对图像计算做出移动指令，最终实现目标路径规划。
采用机器人操作系统（ROS）与Client/Server（客户端/服务端）通信相结合来实现本课题。首先客户端用来接受kinenct所采集的图像，将障碍识别到服务器；其次服务器端实时的对图像进行计算处理，利用机器人跟踪技术,并将产生的控制命令返回给客户端，最终远程实现对机器人的跟踪控制。
关键词：目标跟踪；ROS机器人程序设计；C/S通信框架；远程控制；云机器人
Abstract
The development of intelligent robots has penetrated into the daily aspects of people's daily life, and increasingly plays an important role in people's daily life, and intelligent robot tracking technology is an important research direction in the field of robot research. Cloud computing is being applied to a variety of scenes, the traditional robot computing storage capacity is limited by its onboard equipment, cloud computing and robot combination for the promotion of robot capability is one of the future development trend of the robot.
Based on Python to achieve the robot target tracking, the need to migrate object recognition to the cloud server, cloud service real-time through the image calculation to make mobile instructions, and ultimately achieve the target tracking.
I use the robot operating system (ROS) and Client / Server (client / server) communication to achieve this problem. First, the client is used to accept the image collected by kinenct, and the object is recognized to the server. Secondly, the server realizes the mobile instruction by using the robot tracking technology and returns the result to the server to do the logical processing and generate the control command, The final remote implementation of the robot tracking control.
Key words: target tracking; ROS robot programming; C/S communication framework; remote control; cloud robot
目 录
Research and Prototype Realization of Object Recognition and Tracking Technology for Intelligent
4.3 ROS中sensor_msgs/Image的消息格式
