基于粒子群模糊的除冰机器人越障规划

由于除冰机器人多在天气恶劣,覆冰较厚的输电线路上工作,现有的基于视觉伺服越障策略存在图像质量差,冰、线区分难等不足。根据模糊逻辑和粒子群优化原理,提出了一种除冰机器人在线越障和路径规划方法。该方法通过模糊规划器实现除冰机器人机械臂的无障跟踪和平稳越障。在此基础上,以机械臂末端经过路径长度和与目标点距离的综合最小为目标,利用粒子群算法对模糊规划器输出角度进行在线优化。仿真结果表明:与传统的模糊越障规划相比,该方法不仅满足除冰机器人实时规划和自主越障的要求,缩短了机械臂经过轨迹的长度,提高了除冰机器人的工作效率和续航能力,为实际工程应用中除冰机器人的能源短缺问题,提供了一种节约使用方案,具有一定的工程应用价值。     

一种基于DTW-GMM的机器人多机械臂多任务协同策略

为了控制机器人完成复杂的多臂协作任务, 提出了一种基于动态时间规整?高斯混合模型(Dynamic time warping-Gaussian mixture model, DTW-GMM)的机器人多机械臂多任务协同策略. 首先, 针对机器人示教时轨迹时间长短往往存在较大差异的问题, 采用动态时间规整方法来统一时间的变化; 其次, 基于动态时间规整的多机械臂示教轨迹, 采用高斯混合模型对轨迹的特征进行提取, 并以某一机械臂的位置空间矢量作为查询向量, 基于高斯混合回归泛化输出其余机械臂的执行轨迹; 最后, 在Pepper仿人机器人平台上验证了所提出的多机械臂协同策略, 基于DTW-GMM算法控制机器人完成了双臂协作搬运任务和汉字轨迹的书写任务. 提出的基于DTW-GMM算法的多任务协同策略简单有效, 可以利用反馈信息实时协调各机械臂的任务, 在线生成平滑的协同轨迹, 控制机器人完成复杂的协作操作.     

机械臂轨迹跟踪控制--基于EC-RBF神经网络的机械臂模型参考自适应控制

针对机械臂运动轨迹控制中存在的跟踪精度不高的问题,采用了一种基于EC-RBF神经网络的模型参考自适应控制方案对机械臂进行模型辨识与轨迹跟踪控制。该方案采用了两个RBF神经网络,运用EC-RBF学习算法,采用离线与在线相结合的方法来训练神经网络,一个用来实现对机械臂进行模型辨识,一个用来实现对机械臂轨迹跟踪控制。对二自由度机械臂进行仿真,结果表明,使用该控制方案对机械臂进行轨迹跟踪控制具有较高的控制精度,且因采用EC-RBF学习算法使网络具有更快的训练速度,从而使得控制过程较迅速。     

输电线除冰机器人越障

近年来,我国南方各地连年发生大雪灾,给国家和人民带来了不可估量的损失,尤其是对输电设施的影响,许多高压线铁塔因为覆冰被压塌,高压线因为覆冰被压断。很多高压线除冰的方法已经被研究出来或正在研究中,比如电流融化法、敲击法、铣削法,这几种方法各有千秋。该越障式除冰机器人集越障、除冰、防冰于一体,还能实现自平衡,提高除冰的工作效率,实现最大程度的智能化,且降低了劳动强度。最主要的特点更在于它自身的越障方式,使用双滚轮和圆盘相结合的越障方式,更是在传统"三臂除冰机器人"上的创新和突破。     

多关节机械臂轨迹跟踪自适应神经网络滑模控制

针对不确定干扰和建模误差对多关节机械臂轨迹跟踪控制系统造成的不良影响,对基于滑模控制的自适应神经网络滑模控制算法进行了研究。通过神经网络,对多关节机械臂轨迹跟踪控制系统的不确定干扰和建模误差进行逼近。添加自适应项,补偿神经网络滑模控制中神经网络模型对系统中的不确定干扰和建模误差的逼近误差。设计了具有指数趋近律的滑模面,以提升多关节机械臂轨迹跟踪控制系统的鲁棒性和响应速度。使用李雅普诺夫稳定性理论,证明了多关节机械臂轨迹跟踪控制系统的半全局稳定性,并通过MATLAB对理论结果进行了仿真验证。仿真结果表明,对具有不确定干扰和建模误差的多关节机械臂轨迹跟踪控制系统,采用该算法进行轨迹跟踪时,具有较好的稳定性与鲁棒性。该控制算法能合理应用到此类轨迹跟踪控制系统中。     

双臂机器人协调轨迹滑模鲁棒控制算法研究

双臂机器人控制时,受模型精度、外界扰动、关节柔性等因素影响严重,为了降低内外部因素对双臂协调控制性能的干扰,提出了一种关节轨迹滑模鲁棒控制算法.由于滑模控制善于求解非确定系统,因此适用于难以获得精确模型,且外界扰动未知的机械臂协调控制.在机械臂动力模型与偏差分析的基础上,把关节惯性、离心和重力表示为轨迹控制时的预期输出量,控制力矩表示为鲁棒因子,并根据角位置偏差设计滑模变量与指数趋近律.为避免滑模控制产生抖振,引入自整定边界层,使滑模控制机械臂轨迹收敛于边界层,计算得到最终的控制量与扰动量.基于与构造双臂机器人仿真模型,实验结果验证了关节轨迹滑模鲁棒控制算法能够抑制双臂机器人动作时受到的内外部扰动,避免发生系统抖振现象,有效提高机械臂的控制准确性与稳定性,获得更加协调稳定的双臂运动轨迹.     

基于细菌觅食算法的嵌入式机械臂角度控制器设计

进行机械臂角度控制器设计过程中,为提高机器人机械臂灵活性,降低关节角度控制误差,设计一种细菌觅食算法的嵌入式机械臂角度控制器。首先,构建机械臂动力学模型以获取机械臂的柔性特征及其关节位置,根据获取的信息确定角度控制器的硬件逻辑结构和算法。然后,使用ARM微处理器嵌入式操作系统,设计包含移动控制终端和机械臂控制端的控制器硬件结构。最后,采用细菌觅食算法优化控制器参数,并实现代码完成机器人机械臂角度的精准跟踪控制。仿真分析结果表明:所提方法具有较高的位姿跟踪精度、角度控制误差小、稳定性强,能够保证机械臂关节角度无超调,具有极高的机器工程应用价值。     

基于三步法的机械臂轨迹跟踪控制

考虑机械臂末端轨迹跟踪控制问题,以跟踪逆运动学求解出的末端期望轨迹对应的各关节期望角度为控制目标.设计了一种基于三步法的控制器,该控制器由类稳态控制、可变参考前馈控制和误差反馈控制3部分组成.证明了该控制器可以通过控制机械臂的各关节力矩实现各关节实际角度对期望角度的状态跟踪,进而使得末端轨迹渐近跟踪期望轨迹,并且跟踪误差是输入到状态稳定的.仿真表明基于三步法控制器的空间机械臂末端可以渐近跟踪期望轨迹,并且该算法可以克服系统的末端负载质量变化等不确定性的影响.     

基于双向LSTM神经网络的机器人机械臂智能轨迹控制系统

针对机械臂智能轨迹控制易受其不确定性与外部扰动影响的问题,设计基于双向LSTM神经网络的机器人机械臂智能轨迹控制系统,实现对机器人机械臂轨迹的实时控制,使其能够快速响应环境变化和执行新任务。利用远程控制模块输入用户设定的机械臂运行参数;主控制模块的主控单元利用双向LSTM神经网络,估计机械臂的不确定性数据,并依据用户设定的相关参数,结合自适应滑模控制器,设计机械臂智能轨迹复合控制律,由主站通讯板卡传输至伺服模块;伺服模块接收智能轨迹复合控制律后,利用伺服驱动器启动直流力矩电机,按照复合控制律驱动机械臂运动,完成机械臂智能轨迹控制。实验证明：该系统可有效完成机器人机械臂智能轨迹控制,且控制后的运行轨迹与设定轨迹非常接近;经过控制后的机械臂关节角度变化曲线较平滑,且连续,具备较优的智能轨迹控制效果。     

基于蚁群算法的机械臂轨迹偏离自动控制方法

常规的机械臂轨迹偏离自动控制方法使用相关的控制算法对偏离的轨迹进行补偿跟踪,无法控制移动的姿态轨迹,导致机械臂轨迹偏离值过高,因此需要基于蚁群算法,设计一种全新的机械臂轨迹偏离自动控制方法。以自动化执行网络为基础,获取最优控制反馈,生成偏离控制器,再输出控制参数,形成控制轨迹模型,得到轨迹偏离自动控制算法,从而实现机械臂轨迹偏离自动控制。实验结果表明,设计的基于蚁群算法的机械臂轨迹偏离自动控制方法在不同测试点下的轨迹偏离值均较低,证明设计方法的自动控制效果较好,具有有效性,有一定的应用价值。     

Obstacle avoidance tracking control with antiswing and tracking errors constraint for underactuated automated lifting robots with load hoisting/lowering

The existing automated lifting robot technology focuses merely on motion control and ignores the surrounding environment. In practice, obstacles inevitably exist in the movement path of the automated lifting robot, which affects construction safety. Furthermore, due to the underactuated characteristics of the automated lifting robot, the load can be difficult to control when it swings violently, which undoubtedly poses huge challenges to obstacle avoidance trajectory planning and controller design. In this paper, an obstacle avoidance trajectory and its tracking controller with antiswing and tracking errors constraint are proposed. To ensure accurate load positioning and effective obstacle avoidance, the proposed control method introduces a four-segment polynomial trajectory interpolation curve to construct an obstacle avoidance trajectory based on analyzing the geometric relationship between variables. To improve the transient coupling control performance of the system, combined with the passive analysis of the automated lifting robot system, this method constructs a potential function that limits the tracking error and a coupling signal that enhances the coupling relationship between the system variables. Barbalat's lemma and Lyapunov techniques are used to analyze the stability of the system. Simulation and experimental results show that the proposed control method can significantly suppress or even eliminate load oscillation, accurately locate the load, avoid obstacles, improve the safety and efficiency of the working automated lifting robot, and have strong robustness to changes in system parameters and the addition of external disturbances.     

载人机器人平顺轨迹规划及自抗扰跟踪控制方法

针对公共环境载人机器人的安全性和乘载舒适性需求,提出一种机器人平顺轨迹规划及改进自抗扰跟踪控制方法,重点解决避险和平稳运动两种工况下机器人轨迹扰动问题;首先,设计了基于障碍物密度及其危险性的在线速度空间优化方法,获得符合安全和舒适度要求的轨迹;其次,采用扩张状态观测器观测机器人轨迹跟踪过程中内外扰动并实施补偿;再次,引入非线性反馈控制律自动调整反馈增益,减少超调并提高自抗扰控制器稳定性;对不同场景数值模型仿真表明,提出的轨迹规划方法可以满足机器人作业的安全性、舒适性需求;改进自抗扰跟踪控制器效果明显优于传统ADRC和自适应PID,具有较强的抗干扰能力和较快速的跟踪性能.     

加入临时路径的移动机器人路径跟踪模糊控制

对含不确定性的移动机器人系统设计了路径跟踪模糊控制方法。该方法引入临时路径,使机器人先从初始位置出发沿临时路径行进,当移动到期望路径附近时,再让机器人跟踪期望路径。整个控制过程只需要一个模糊控制器,极大地减少了工作量,并引进积分环节以消除稳态误差。仿真和实验结果验证了该方法的有效性。     

Navigation of Mobile Robots Using a Fuzzy Logic Controller

This paper describes a mobile robot navigation control system based on fuzzy logic. Fuzzy rules embedded in the controller of a mobile robot enable it to avoid obstacles in a cluttered environment that includes other mobile robots. So that the robots do not collide against one another, each robot also incorporates a set of collision prevention rules implemented as a Petri Net model within its controller. The navigation control system has been tested in simulation and on actual mobile robots. The paper presents the results of the tests to demonstrate that the system enables multiple robots to roam freely searching for and successfully finding targets in an unknown environment containing obstacles without hitting the obstacles or one another.     

含有摩擦补偿的全方位移动机器人自抗扰控制

本文针对全方位移动机器人轨迹追踪中的摩擦补偿问题,提出了一种改进的非线性自抗扰控制器.首先建立了含有经典静态摩擦模型的全方位移动机器人动力学模型.其次,基于该模型设计非线性控制器和线性扩张状态观测器并给出了系统的稳定性分析.通过将模型已知项加入线性扩张状态观测器中得到摩擦力的估计值,并将估计值用于非线性控制器中摩擦补偿部分.为减小摩擦力对机器人低速运动轨迹追踪控制的影响,非线性控制器采用变增益控制器进行轨迹追踪控制.最后通过仿真结果验证本文提出控制器的有效性.     

Mobile robot path planning and tracking using simulated annealing and fuzzy logic control

This article describes the development and implementation of an automatic controller for path planning and navigation of an autonomous mobile robot using simulated annealing and fuzzy logic. The simulated annealing algorithm was used to obtain a collision-free optimal trajectory among fixed polygonal obstacles. C-space was used to represent the working space and B-spline curves were used to represent the trajectories. The trajectory tracking was performed with a fuzzy logic algorithm. A detailed explanation of the algorithm is given. The objectives of the control algorithm were to track the planned trajectory and to avoid collision with moving obstacles. Simulation and implementation results are shown. A Nomadic 200 mobile robot was used to perform the experiments.     

Obstacle Modelling Oriented to Safe Motion Planning and Control for Planar Rigid Robot Manipulators

Trajectory planning and tracking are crucial tasks in any application using robot manipulators. These tasks become particularly challenging when obstacles are present in the manipulator workspace. In this paper a n-joint planar robot manipulator is considered and it is assumed that obstacles located in its workspace can be approximated in a conservative way with circles. The goal is to represent the obstacles in the robot configuration space. The representation allows to obtain an efficient and accurate trajectory planning and tracking. A simple but effective path planning strategy is proposed in the paper. Since path planning depends on tracking accuracy, in this paper an adequate tracking accuracy is guaranteed by means of a suitably designed Second Order Sliding Mode Controller (SOSMC). The proposed approach guarantees a collision-free motion of the manipulator in its workspace in spite of the presence of obstacles, as confirmed by experimental results.     

A Smith-predictor-based generalised predictive controller for mobile robot path-tracking

This paper shows how to improve the robustness of mobile robot path tracking when predictive control algorithms are used. When uncertainties in a mobile robot are considered, it is shown how the classical generalised predictive controller (GPC) may lead to an unstable behaviour of the mobile robot. The equivalence between the GPC and a structure composed by an optimal predictor and a classical controller is given, and it is shown that use of a Smith predictor instead of an optimal predictor increases the robustness of the system. A new strategy, the Smith-predictor-based GPC, is proposed. Experimental tests carried out on a LABMATE mobile robot validate the performance of the proposed controller.     

基于Lyapunov方法和快速终端滑模的轨迹跟踪控制

针对移动机器人的运动学模型,提出一种具有全局渐近稳定性的跟踪控制器。该跟踪控制器的设计分为两部分：第一部分是采用全局快速终端滑动模态的思想设计了角速度的控制律,用来渐近镇定移动机器人跟踪的前向角误差;第二部分是采用Lyapunov方法设计了线速度的控制律,用来渐近镇定移动机器人跟踪的平面坐标误差。采用Lyapunov稳定性定理,证明了移动机器人在满足这些控制律条件下,实现了对参考轨迹的全局渐近跟踪。实验结果表明移动机器人能够有效地跟踪期望轨迹,有利于在实际应用中推广。     

Trajectory tracking control of mobile robots without using longitudinal velocity measurements

We propose a new robust trajectory tracking control scheme for wheeled mobile robots without longitudinal velocity measurements. In the proposed controller, a velocity observer is used to estimate the longitudinal velocity of a wheeled mobile robot. A wheeled mobile robot model, including motor dynamics, is used to develop the controller. The developed controller has the following useful properties. (1) The developed controller does not require any accurate knowledge of the robot parameters or the motor parameters. Even if there are uncertainties in the robot dynamics, including the motor properties, it is certain that tracking errors ultimately become uniformly bounded in a closed-loop system using the developed controller. (2) It is shown theoretically that the ultimate norms of tracking errors can easily be reduced by setting only one design parameter.