滑动与打滑条件下的轮式移动机器人自抗扰跟踪控制

针对具有未知的滑动与打滑的轮式移动机器人(WMR),提出了一种基于自抗扰思想的跟踪控制策略.首先建立了滑动与打滑条件下的轮式移动机器人动力学模型.其次,由反步法设计运动学控制器,基于模型设计线性扩张观测器和动力学控制器,并给出了控制器稳定性分析.最后与积分滑模控制进行了仿真对比,结果表明该控制方法的误差收敛速度更快.观测器能够精确估计滑动与打滑及动力学不确定性对机器人的扰动,提高了轮式移动机器人轨迹跟踪的鲁棒性.     

移动机器人滑动参数定界及鲁棒镇定控制

本文针对带运动学参数不确定性的野外轮式移动机器人模型的在线辨识、定界和点镇定控制问题展开了研究.考虑了移动机器人二维平面运动过程中所存在的滑动效应和自身几何参数未知等不确定性,并将其建模为运动学模型中所包含的未知时变参数.通过引入基于有界误差假设的非线性集员滤波方法,对移动机器人运动学模型中存在的不确定性参数进行了辨识和定界.在此基础上结合backstepping控制思想和Lyapunov分析方法解决了移动机器人的鲁棒镇定问题,在存在滑动参数干扰的情况下实现了移动机器人的全局指数收敛点镇定控制,提高了整体控制系统的稳定性和鲁棒性.仿真结果证明了本方法的有效性和鲁棒性.     

基于UKF的移动机器人主动建模及模型自适应控制方法

利用基于无色卡尔曼滤波（Unscented Kalman Filter, UKF）的状态和参数联合估计方法对移动机器人进行在线主动建模,基于该主动模型的逆动力学控制方法,实现了移动机器人对其自身不确定因素的自主性. 在针对全方位移动机器人的仿真实验中,验证了UKF对时变的状态和参数的收敛性和跟踪能力,并给出了不确定界. 基于主动建模的逆动力学控制方法与常值PID控制方法的比较结果,验证了该方法的有效性.     

UHF-RFID环境下的移动机器人定位方法

研究UHF-RFID环境中移动机器人的定位问题,提出一种基于自适应UKF滤波器组的移动机器人定位方法,融合UHF-RFID和机器人内部传感器信息,以实现初始位姿未知的移动机器人定位.首先,利用UHF-RFID系统对移动机器人进行初始定位,并根据其初始位置信息随机生成移动机器人的初始状态估计集;然后,考虑UHF-RFID系统定位的量化误差,应用自适应UKF方法对机器人的状态估计集进行预测和更新,并对状态估计集进行有效地裁剪、筛选以及更新,以提高滤波器的估计精度和稳定性.仿真结果表明,相比于标准UKF滤波方法,自适应UKF滤波器组方法具有更高的定位精度和更快的收敛速度.     

基于旋量理论的移动机器人建模与控制

为了解决移动机器人由于系统中存在不可积运动约束,不能直接应用旋量理论建模的问题,通过构造虚拟连杆首先把移动机器人转化成等价的固定基单自由度关节的开链机器人,然后基于运动旋量理论建立了移动机器人的运动模型,为移动机器人系统建模提供了一个简洁的新途径.基于所建立的移动机器人运动模型,设计了一个稳定的输出跟踪控制器.在Matlab下对移动机器人的建模和控制进行了仿真,验证了所提出的建模方法的可行性.     

移动机器人编队的递归模糊神经网络滑模控制

研究非完整移动机器人编队控制优化问题,由于动态模型存在诸多不稳定性,针对领航者-跟随者l-ψ控制结构,提出了一种Back stepping运动学控制器与自适应神经滑模控制器相结合的新型控制策略.采用动态递归模糊神经网络(dynam-ic recurrent fuzzy neural network,DRFNN)对跟随者及领航者动力学非线性不确定部分进行在线估计,并通过自适应鲁棒控制器对神经网络建模误差进行补偿.所提方法不但解决了移动机器人编队控制的参数与非参数不确定性问题,同时也确保了机器人编队在期望队形下对指定轨迹的跟踪;根据Lyapunov方法的设计过程,保证了控制系统的稳定;仿真结果表明了改进方法对机器人编队优化控制的有效性.     

未知环境下移动机器人地图构建仿真研究

未知环境的地图构建是移动机器人研究领域的一个研究热点.为了研究在未知环境下移动机器人地图构建,基于微软机器人开发工作室(MRDS),对虚拟环境中移动机器人进行了仿真建模,通过激光测距仪获取未知环境信息,应用迭代最近点(ICP)算法处理未知环境信息实现了移动机器人对未知环境地图构建.对移动机器人地图构建仿真实验结果表明,文中的方法能够有效地实现未知环境地图构建,可为移动机器人运动提供导向作用,具有一定的理论和现实意义.     

基于改进角度直方图和最小二乘法的移动机器人地图构建

本文主要研究完全未知结构化环境下的移动机器人二维几何地图构建及其不确定性描述问题.在考虑测量噪声干扰的基础上,基于改进的角度直方图算法进行环境线段特征提取和参数初始估计,然后利用加权最小二乘法对线段特征参数及其方差进行精确估计,并同时给出了多位姿地图合并的处理方法.文章最后给出了在SmartROB2机器人平台上进行的实验结果,证明了算法的有效性和实用性.     

含驱动器动力学的移动机器人编队自适应控制

针对含有驱动器及编队动力学的多非完整移动机器人编队控制问题,基于领航者-跟随者[l-ψ]控制结构,通过反步法设计了一种将运动学控制器与驱动器输入电压控制器相结合的新型控制策略。采用径向基神经网络（RBFNN）对跟随者及领航者动力学非线性不确定部分进行在线估计,并通过自适应鲁棒控制器对神经网络建模误差进行补偿。该方法不但解决了移动机器人编队控制的参数与非参数不确定性问题,同时也确保了机器人编队在期望队形下对指定轨迹的跟踪;基于Lyapunov方法的设计过程,保证了控制系统的稳定与收敛;仿真结果表明了该方法的有效性。     

两轮差速移动机器人系统误差调校研究

两轮差速移动机器人的运动学缺陷会导致系统误差,影响机器人的导航和定位精度。为了降低移动机器人系统误差对定位精度的影响,对校准两轮差速移动机器人系统误差的方法进行了研究。通过机器人定距直线往返运动所产生的位置偏差,获得校准参数。采用直线和双方形封闭环路径试验,对调校参数有效性进行验证。试验结果表明:调校后移动机器人的位置偏差显著改善,调校后位置偏差改善程度分别达98.24%和97.35%。该运动学参系统误差调校方法为移动机器人数精确估计和里程调校精度的提高提供了理论参考。     

Modeling of tracked mobile manipulators with consideration of track–terrain and vehicle–manipulator interactions

This paper presents a systematic method to establish the kinematics model for a tracked mobile manipulator on firm grounds, with consideration of the interactive motions between the tracks and the terrain, as well as those between the tracked vehicle and the onboard manipulator. Kinematics analysis is essential for real-time pose estimation and online autonomous navigation of tracked mobile manipulators. Furthermore, to improve the effectiveness of motion planning, and to simulate or control tracked mobile manipulators, a reliable kinematics model is required. However, kinematics modeling for a tracked mobile manipulator is complicated by the fact that there are infinite number of contact points between the tracks and the terrain, which makes slippage unavoidable. The track–terrain and vehicle–manipulator interactions make the problem even more complicated as the motion of the onboard manipulator and the centrifugal forces during moderate or high speed motion give rise to transfer of the load distribution, which will affect the longitudinal and lateral tractive forces and the resistance. Also, the motion of the mobile platform contributes to the inertial forces of the manipulator, and the track–terrain interactive forces help balance the gravity as well as the manipulation forces. The developed kinematics modeling approach is presented on the basis of a tracked mobile manipulator in our laboratory, but the forward kinematics analysis method, and the track–terrain and vehicle–manipulator interaction analysis algorithm are general, and can be used for any tracked mobile manipulators with little modification. This work lays a solid foundation for autonomous control, online slippage estimation, real-time traction optimization as well as tip-over prediction and prevention of tracked mobile manipulators.     

轮子纵向打滑条件下的移动机器人自适应跟踪控制

针对纵向滑动参数未知的轮式移动机器人的轨迹跟踪问题,提出一种自适应跟踪控制策略.利用两个未知参数来描述移动机器人左右轮的纵向打滑程度,建立了产生纵向滑动的差分驱动轮式移动机器人的运动学模型;设计了补偿纵向滑动的自适应非线性反馈控制律;应用 Lyapunov 稳定性理论与 Barbalat 定理证明了闭环系统的稳定性;同时,提出了一种由极点配置方法在线调整控制器增益的方法.仿真结果验证了所提出控制方法的有效性.     

履带式移动机器人轨迹跟踪研究

详细分析了履带式移动机器人的受力特点,提出了一种适宜进行控制器设计的履带移动机器人模型.根据履带式移动机器人动力学模型和运动学模型,设计了机器人的轨迹跟踪控制器.利用Lyapunov稳定判据证明控制器的全局稳定性.在控制器的设计中考虑了履带一地面作用,引入参数对其描述.考虑到机器人动力学约束,引入机器人速度、加速度控制策略以保证机器人运动平滑.仿真实验验证了该方法的有效性和全局收敛.     

基于传感器信息融合的移动机器人自主爬楼梯技术研究

机器人自主爬楼梯是移动机器人完成危险环境探查、侦察、救灾等任务需要具备的基本智能行为之一.分析了楼梯的多样性和履带式机器人爬楼梯固有的不稳定性导致机器人爬楼梯工作的复杂性,描述了带前导手臂的履带式移动机器人爬楼梯的步骤,简要介绍了利用超声波、视频摄像头和激光扫描测距仪信息来感知楼梯和判断机器人与楼梯相对位置的算法,最后提出了一个基于传感器测量值可信度的信息融合方法进行楼梯参数感知和行驶方向计算的机器人自主爬楼梯的控制系统结构.     

Mobile robot localization with gyroscope and constrained Kalman filter

The odometry information used in mobile robot localization can contain a significant number of errors when robot experiences slippage. To offset the presence of these errors, the use of a low-cost gyroscope in conjunction with Kalman filtering methods has been considered by many researchers. However, results from conventional Kalman filtering methods that use a gyroscope with odometry can unfeasible because the parameters are estimated regardless of the physical constraints of the robot. In this paper, a novel constrained Kalman filtering method is proposed that estimates the parameters under the physical constraints using a general constrained optimization technique. The state observability is improved by additional state variables and the accuracy is also improved through the use of a nonapproximated Kalman filter design. Experimental results show that the proposed method effectively offsets the localization error while yielding feasible parameter estimation.     

System centroid position based tipover stability enhancement method for a tracked search and rescue robot

Tipover may cause fatal damages to the mobile robot system during obstacle crossing or stair climbing, and the system centroid position (SCP) is very important for the tipover stability. By monitoring the SCP, it is possible to estimate the risk of tipover and take appropriate actions to prevent the incident from happening. This paper proposes a new tipover avoidance method for enhancing the tipover stability of a tracked mobile manipulator by online adjusting the SCP. The tipover stability criteria for the robot are discussed based on the orientation data from a three-axial gyroscope and the SCP calculation. The velocity kinematic model of the manipulator for SCP adjustment is also presented in this paper. In addition, a redundancy resolution method is employed in order to improve the performance of the robot. The proposed method is applied to a search and rescue robot consists of a four degree of freedom manipulator and a tracked mobile base, and the effectiveness of this method is demonstrated by experimental results.     

Switched Modeling and Task–Priority Motion Planning of Wheeled Mobile Robots Subject to Slipping

This study is devoted to the modelling and control of Wheeled Mobile Robots moving with longitudinal and lateral slips of all wheels. Due to wheel slippage we have to deal with systems with changing dynamics. Wheeled Mobile Robots can be thus modeled as switched systems with both autonomous switches (due to wheel slippage) and smooth controls (due to control algorithm). It is assumed that the slipping is counteracted by the slip reaction forces acting at contact points of the wheels with the ground. A model of these reaction forces, borrowed from the theory of automotive systems, has been adopted and included into the Lagrangian dynamic equations of the robot. A framework for designing motion planning schemes devoid of chattering effects for systems with changing dynamics is presented. A task–priority motion planning problem for wheeled mobile robots subject to slipping is addressed and solved by means of Jacobian motion planning algorithm based on the Endogenous Configuration Space Approach. Performance of the algorithm is presented in simulations of the Pioneer 2DX mobile platform. The robot dynamics equations are derived and 4 variants of motion are distinguished. The motion planning problem is composed of two sub-tasks: robot has to reach a desired point in the task space (proper motion planning) and the motion should minimize either the control energy expendinture or the wheel slippage. Performance of the motion planning algorithm is illustrated by a sort of the parking maneuver problem.     

基于CPLD的彩色视觉移动机器人路径跟踪系统

路径跟踪是机器人视觉导航控制基本技术之一,为使机器人沿地面彩色引导线自主运动,并能在适时离线执行任务后自动返航,提出了一种用可编程逻辑器件(CPLD)实现的视觉伺服PID控制方法.该方法利用图像特征反馈对其所跟踪的路经进行实时识别跟踪.仿真结果表明,该方法改善了控制算法的实时性,提高了移动机器人的路径跟踪精度与速度.     

Distributed Control of Nonholonomic Robots Without Global Position Measurements Subject to Unknown Slippage Constraints

This paper studies the fully distributed formation control problem of multi-robot systems without global position measurements subject to unknown longitudinal slippage constraints.It is difficult for robots to obtain accurate and stable global position information in many cases,such as when indoors,tunnels and any other environments where GPS(global positioning system)is denied,thus it is meaningful to overcome the dependence on global position information.Additionally,unknown slippage,which is hard to avoid for wheeled robots due to the existence of ice,sand,or muddy roads,can not only affect the control performance of wheeled robot,but also limits the application scene of wheeled mobile robots.To solve both problems,a fully distributed finite time state observer which does not require any global position information is proposed,such that each follower robot can estimate the leader’s states within finite time.The distributed adaptive controllers are further designed for each follower robot such that the desired formation can be achieved while overcoming the effect of unknown slippage.Finally,the effectiveness of the proposed observer and control laws are verified by simulation results.     

可重构模块机器人倾翻稳定性研究

介绍了一种可重构模块机器人,它可以通过构形的变化来提高系统的稳定性和抗倾翻能力．该机器人由3个模块组成,采用履带驱动,具有直线、三角、并排3种对称构形．在对移动机器人的倾翻因素和倾翻对策等问题进行分析的基础上,提出稳定锥方法,用倾翻性能指数对移动机器人的静、动态稳定性进行综合判定. 讨论了变形机器人3种对称构形在仰俯、偏转、倾斜等干扰组合作用下的倾翻性能指数和综合稳定性,并进行了仿真实验和非结构环境实验．