可分离式立体侦察机器人运动控制研究

发布时间：2018-08-30 07:48

【摘要】：随着互联网、人工智能等高新科技的飞速发展,侦察机器人系统在军事、消防、救灾、勘探等领域获得了广泛的应用。目前,国内外在研、在用的侦察机器人系统分为空中侦察机器人系统和陆地侦察机器人系统两大系列,均具有明显的优势特点,本文设计一种可分离式立体侦察机器人,兼顾空中飞行与地面移动行走,实现了陆域、空域协同立体式侦察,是对现有侦察机器人体系的有利补充。首先,设计了可变形履带式机器人与四旋翼无人机相结合的方案,采用磁力锁吸合与多自由度机械手臂抓取的物理结构,实现两者之间的快速分离与刚体结合,同时设计了空中飞行控制系统与地面移动行走控制系统,采用MQTT(Message Queuing Telemetry Transport,消息队列遥测传输)协议作为远端姿态控制协议。其次,通过牛顿-欧拉法建立机器人姿态角解算模型,描述其横滚角、俯仰角和偏航角三种飞行姿态角,根据模型建立系统状态方程和观测方程,采用改进型的卡尔曼滤波算法——无色卡尔曼滤波算法与扩展卡尔曼滤波算法进行姿态角解算,并通过Matlab仿真对比,验证无色卡尔曼滤波算法与扩展卡尔曼滤波算法的姿态角解算精度与实时性,对比仿真结果表明,无色卡尔曼滤波算法比扩展卡尔曼滤波算法姿态角估计精度更高、实时性更强,最终采用无色卡尔曼滤波算法进行姿态角解算,得到飞行姿态角最优估计值,并应用于实际飞行控制系统中。最后,研制出侦察机器人样机,实现了高空飞行、地面移动、爬坡、语音控制、远端语音视频回传,以及四旋翼无人机与履带式机器人的智能结合与智能回收等功能,并在实际环境中对样机的性能与功能进行测试,测试结果表明,该款侦察机器人克服了传统侦察机器人系统面临的地形受限问题,具备良好的侦察地形适应能力,机动性良好,通信距离远,综合侦察作业时间长,真正做到立体式全方位侦察,提高了无人侦察的效率。
[Abstract]:With the rapid development of the Internet, artificial intelligence and other high-tech, reconnaissance robot system has been widely used in military, fire, disaster relief, exploration and other fields. At present, at home and abroad, the reconnaissance robot system in use is divided into two series: aerial reconnaissance robot system and land reconnaissance robot system, both of which have obvious advantages. In this paper, a separable stereo reconnaissance robot is designed. Combined aerial flight and ground moving walking, the cooperative stereo reconnaissance in land and airspace is realized, which is a favorable supplement to the existing reconnaissance robot system. Firstly, the scheme of deformable crawler robot and four-rotor UAV is designed, which adopts the physical structure of magnetic lock and multi-degree-of-freedom mechanical arm to realize the quick separation and rigid body combination between the two. At the same time, the air flight control system and the ground mobile walking control system are designed. The remote attitude control protocol is based on the MQTT (Message Queuing Telemetry Transport, message queue telemetry transmission protocol. Secondly, by Newton-Euler method, the attitude angle calculation model of the robot is established, and the three flight attitude angles of roll angle, pitch angle and yaw angle are described, and the system state equation and observation equation are established according to the model. An improved Kalman filter algorithm, colorless Kalman filter, and extended Kalman filter algorithm are used to calculate the attitude angle, and the simulation results are compared by Matlab. The accuracy and real time of attitude angle estimation of colorless Kalman filter and extended Kalman filter are verified. The simulation results show that the accuracy of attitude angle estimation of colorless Kalman filter is higher than that of extended Kalman filter. Finally, the colorless Kalman filter algorithm is used to calculate the attitude angle, and the optimal estimation value of the flight attitude angle is obtained, which is applied to the actual flight control system. Finally, a prototype reconnaissance robot is developed, which realizes the functions of high altitude flight, ground movement, slope climbing, voice control, remote voice and video return, intelligent combination and intelligent recovery of four-rotor UAV and crawler robot, etc. The performance and function of the prototype are tested in the actual environment. The test results show that the reconnaissance robot overcomes the problem of terrain limitation faced by the traditional reconnaissance robot system, has good adaptability to reconnaissance terrain, and has good maneuverability. The communication distance is long, the integrated reconnaissance operation time is long, and the stereoscopic omnidirectional reconnaissance is really achieved, and the efficiency of unmanned reconnaissance is improved.
【学位授予单位】：西安邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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