基于超宽带测距的异构移动机器人轨迹跟踪控制

doi:10.13700/j.bh.1001-5965.2017.0526

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摘要针对超宽带（UWB）测距过程中随机出现的奇异值，设计了改进的基于最小协方差的马氏距离奇异值检测模块；针对全向机器人的运动学和动力学特点，提出了一种基于滑模+PID控制的逆动力学前馈轨迹跟踪算法；针对UWB定位算法中出现的坐标跳动、边缘效应以及微型四旋翼的运动学特点，设计了基于扩展卡尔曼滤波（EKF）的轨迹跟踪控制算法；并在MATLAB和Gazebo仿真软件中分别进行了验证。为在实际环境验证轨迹跟踪控制算法的速度闭环控制和位置闭环控制以及UWB定位的实时性、准确性，搭建了基于UWB的异构多机器人系统，完成了四旋翼定点悬停、单个全向机器人轨迹跟踪、异构多机器人协同控制实验。实验结果表明，UWB定位系统和机器人控制算法能够满足控制的实时性和稳定性要求。

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	卫恒
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关键词 ：超宽带(UWB), 马氏距离, 全向机器人, 微型四旋翼, 轨迹跟踪, 多机器人系统

Abstract：Aimed at random occurrence of singular value in the process of ultra wide band (UWB) ranging, the traditional Mahalanobis distance detection algorithm is improved, and the Mahalanobis distance singular value detection module based on minimum covariance is designed. Based on the omnidirectional robots' kinematic and dynamic characteristics, the inverse dynamic feedforward trajectory tracking algorithm based on sliding mode control and PID control is proposed. Aimed at the coordinate jump, the edge effect and the kinematic characteristics of the micro four rotor in UWB positioning algorithm, a trajectory tracking control method based on extended Kalman filter (EKF) is designed. In MATLAB and Gazebo simulation software, the tracking control algorithm of omnidirectional robot and nano-quadrotor is verified. In order to verify the real-time feature and accuracy of the closed-loop velocity and position control and UWB positioning for trajectory tracking control algorithm in real environment, a heterogeneous multi-robot system based on UWB was built to complete the nano-quadrotor hovering, single omnidirectional robot trajectory tracking, and heterogeneous multi-robot cooperative control experiments. The experimental results show that the UWB positioning system and the robot control algorithm can meet the requirements of real-time and stable control.

Key words： ultra wide band (UWB) Mahalanobis distance omnidirectional robot nano-quadrotor trajectory tracking multi-robot system

收稿日期: 2017-08-11

PACS:

TP242

基金资助:国家自然科学基金（61663014）

通讯作者: 吕强.E-mail:rokyou@live.cn E-mail: rokyou@live.cn

作者简介: 卫恒男,博士研究生。主要研究方向：多机器人协同控制、多机器人SLAM;吕强男,博士,教授,博士生导师。主要研究方向：自主移动机器人、计算机视觉、神经网络。王国胜男,博士,副教授,硕士生导师。主要研究方向：移动机器人控制;林辉灿男,博士研究生。主要研究方向：SLAM自主导航、四旋翼飞行器。梁冰女,博士,副教授,硕士生导师。主要研究方向：四旋翼飞行器控制。

引用本文:

卫恒, 吕强, 王国胜, 林辉灿, 梁冰. 基于超宽带测距的异构移动机器人轨迹跟踪控制[J]. 北京航空航天大学学报, 2018, 44(7): 1461-1471.
WEI Heng, LYU Qiang, WANG Guosheng, LIN Huican, LIANG Bing. Trajectory tracking control for heterogeneous mobile robots based on UWB ranging. JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2018, 44(7): 1461-1471.

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http://bhxb.buaa.edu.cn/CN/10.13700/j.bh.1001-5965.2017.0526 或 http://bhxb.buaa.edu.cn/CN/Y2018/V44/I7/1461

[1] SUEOKA S,IRIE T.The study for control of the robot plane with GPS and IMU[J].Journal of Medical Virology,2016,13:417-418.
[2] SASANI S,ASGARI J,AMIRI-SIMKOOEI A R.Improving MEMS-IMU/GPS integrated systems for land vehicle navigation applications[J].GPS Solutions,2016,20(1):89-100.
[3] LI J,SONG N,YANG G,et al.Improving positioning accuracy of vehicular navigation system during GPS outages utilizing ensemble learning algorithm[J].Information Fusion,2017,35(C):1-10.
[4] SAEEDI S,TRENTINI M,SETO M,et al.Multiple-robot simultaneous localization and mapping:A review[J].Journal of Field Robotics,2016,33(1):3-46.
[5] LOPEZ E,GARCIA S,BAREA R,et al.A multi-sensorial simultaneous localization and mapping (SLAM) system for low-cost micro aerial vehicles in GPS-denied environments[J].Sensors,2017,17(4):802.
[6] AGHILI F,SU C Y.Robust relative navigation by integration of ICP and adaptive Kalman filter using laser scanner and IMU[J].IEEE/ASME Transactions on Mechatronics,2016,21(4):2015-2026.
[7] STACHNISS C,KRETZSCHMAR H.Pose graph compression for laser-based SLAM[M]//CHRISTENSEN H,KHATIB O.Robotics research.Berlin:Springer,2017:271-287.
[8] ENDRES F,HESS J,STURM J,et al.3-D mapping with an RGB-D camera[J].IEEE Transactions on Robotics,2017,30(1):177-187.
[9] GAO X,ZHANG T.Unsupervised learning to detect loops using deep neural networks for visual SLAM system[J].Autonomous Robots,2017,41(1):1-18.
[10] CAO J,ZENG B,LIU J,et al.A novel relocation method for simultaneous localization and mapping based on deep learning algorithm[J].Computers & Electrical Engineering,2017,63(10):79-90.
[11] ERYILDITIM A,GULDOGAN M B.A Bernoulli filter for extended target tracking using random matrices in an UWB sensor network[J].IEEE Sensors Journal,2016,16(11):4362-4373.
[12] crazyflie2.0[EB/OL].[2017-04-20].https://www.bitcraze.io.
[13] 张一淳,张雪波,方勇纯,等.基于主动偏心轮的全方位移动机器人航位推算与跟踪控制[J].机器人,2015,37(3):361-368.ZHANG Y C,ZHANG X B,FANG Y C,et al.Dead reckoning and tracking control of omnidirectional mobile robots[J].Robot,2015,37(3):361-368(in Chinese).
[14] MADHUSUDHAN M G.Control of crazyflie nano quadcopter using Simulink[M].Long Beach:California State University,2016.
[15] JAFAROV S M,ZEYNALOV E R,MUSTAFAYEVA A M.Synthesis of robust controller-regulators for omnidirectional mobile robot with irregular movement[J].Procedia Computer Science,2016,102:469-476.
[16] HAMMER F,YUDANTO R,KAI N,et al.Performance evaluation of 3D-position estimation systems[J].IEEE Sensors Journal,2016,16(16):6416-6424.
[17] 阴盼强,路东明,袁渊,等.基于马氏距离的改进非局部均值图像去噪算法[J].计算机辅助设计与图形学学报,2016,28(3):404-410.YIN P Q,LU D M,YUAN Y,et al.An improved non-local means image de-noising algorithm using Mahalanobis distance[J].Journal of Computer-Aided Design & Computer Graphics,2016,28(3):404-410(in Chinese).
[18] ROUSSEEUW P J,DRIESSEN K V.A fast algorithm for the minimum covariance determinant estimator[J].Technometrics,1999,41(3):212-223.