基于语义的软件服务故障自动诊断模型

模仿学习是机器人仿生机制研究的主要内容之一,即通过观察、理解、学习、模仿示教行为实现机器人的仿生特性。基于高斯过程分别表达采集离散示教信号所构成的示教轨迹和含有未知参数策略的模仿轨迹,构建模仿学习方法框架,将概率模型匹配引入到模仿学习中,以KL散度为代价函数比较两种轨迹的概率分布,运用梯度下降法寻求使KL散度最小的最优模仿控制策略,将策略应用于模仿机器人以完成与示教相同的模仿任务。以关节型机器人的机械臂摆动行为模仿为学习任务进行仿真,结果表明基于概率轨迹匹配的模仿学习方法能够实现机械臂摆动行为模仿,学习过程较传统方法简易且学习效果较好。     

一种冗余机械臂的多运动障碍物避障算法

冗余机械臂的避障问题一直是工业机器人应用领域的研究热点之一;为了改进传统避障算法的不足,提出了一种多运动障碍物的避障算法;该算法利用各障碍物的运动状态得到与机械臂之间的最小预测距离,并将其利用雅可比转置矩阵转化为机械臂对应杆件上的躲避速度,再将躲避速度引入梯度投影法中求得机械臂的关节角速度,并通过积分得到避障运动中机械臂的关节角度值,在完成末端轨迹跟踪的同时实现冗余机械臂的实时避障;利用一款七自由度冗余机械臂对该算法进行了仿真验证,结果表明该算法能有效实现冗余机械臂对多运动障碍物的避障。     

基于虚拟样机技术的四足机器人静态稳定步态规划

针对现有技术文献中广泛使用的多种静态稳定步态中速度稳定性与稳定裕度不可兼得的通病,在随动质心的静态步态基础上,利用参数化坐标变换矩阵方法规划出一种四足机器人前进过程中质心以曲线轨迹移动的静态步态方法,使该步态方法以连续性速度运动的过程中保证一定稳定裕度。通过D-H法求得四足机器人的逆运动学坐标变换矩阵,分别在三维空间中对四足机器人的四组足端轨迹方程进行规划,并带入MATLAB软件后以逆运动学方程计算出关节夹角驱动方程,利用步态规划图求出机器人四条腿各自对应的夹角驱动方程以及机体质心轨迹方程。最后在MSC.ADAMS软件中建立四足机器人虚拟样机并对规划的步态进行虚拟仿真,仿真结果验证了该步态对提升四足机器人对于速度连续性以及稳定裕度的提升。     

基于PSO的工业机器人时间-脉动最优轨迹规划

为提高工业机器人的工作效率,并且保持机器人关节平稳运动,提出一种基于粒子群优化算法的时间-脉动最优轨迹规划方案。通过权重法将多目标优化转化为单目标优化,再运用粒子群优化算法得到时间-脉动最优的运动轨迹。轨迹规划中,采用了关节空间五次非均匀B样条插值法,以确保脉动曲线的连续性。最后以GRB4016工业机器人为研究对象进行仿真实验,结果表明,该方案可以得到较理想的运动轨迹,并验证了方案的有效性。     

考虑柔性关节的机械臂自适应运动控制策略研究

具有柔性关节的轻型机械臂因其自重轻、响应迅速、操作灵活等优点,取得了广泛应用。针对具有柔性关节的机械臂系统的关节空间轨迹跟踪控制系统动力学参数不精确的问题,提出一种结合滑膜变结构设计的自适应控制器算法。通过自适应控制的思想对系统动力学参数进行在线辨识,并采用Lyapunov方法证明了闭环系统的稳定性。仿真结果表明,该控制策略保证了机械臂系统对期望轨迹的快速跟踪,具有良好的跟踪精度,系统具有稳定性。     

面向复杂地形的四足机器人步态生成方法

为实现四足机器人在凹凸地形上稳定运动并能选择最大步长的目的,提出了基于稳定裕度的步态规划方法。基于研究对象,建立四足机器人的运动学方程及逆运动学方程,将机器人足端的位置映射为各关节的关节变量;提出工作空间矩阵的概念,将所需克服的地形高度反映到工作空间矩阵中,并选择最优步态区域;依据四足机器人的立足点在质心坐标系下的空间坐标,以纵向稳定裕度为约束条件,在工作空间矩阵中计算机器人摆动腿的最大步长并规划机械腿的运动轨迹;针对所提出的方法,分别利用MATLAB和ADAMS进行仿真验证。在MATLAB环境中计算并验证质心的水平投影是否在立足点形成支撑多变形内,而ADAMS平台分析机器人在复杂地形上的位移变化及姿态变化。仿真结果表明机器人的质心始终在支撑多边形内,机器人的躯干姿态基本保持不变且运动速度匀速,所提出的方法能够保证机器人稳定行走,为四足机器人的稳定运动提出依据。     

移动平台超短基线阵实现水下目标高精度定位

针对自主式水下航行器如AUV (Autonomous Underwater Vehicle)等水下移动平台,提出了一种超短基线多元阵的快速收敛的高精度声定位方法。通过对比超短基线多元阵定位误差的克拉美罗下界,对阵型结构和阵元数目进行了优化,确定优化的阵列为9元立方阵;融合移动平台行进过程中的多次定位结果,进一步降低定位误差;并利用梯度下降法实现平台轨迹优化,使得系统最快收敛到需要的定位精度。仿真结果表明,在1000 m距离内,利用优化轨迹可以将定位均方根误差快速收敛至预设的0.2%以内.此外,对于海试实验采集数据的目标定位结果显示,对距基阵约700 m及400 m的目标,5元阵定位标准差相较4元阵缩小了约2 m及1 m,验证了多元阵定位方法在实际海洋环境中的有效性.      

新型智能球罐焊接机器人视觉传感器的研究

为实现智能球罐焊接机器人的自主运动与焊缝自动跟踪 ,研制了一种新型视觉传感器。该传感器以高分辨率线阵 CCD芯片为核心 ,由光源、滤光片、透镜等光学系统及 CCD驱动电路、光电信号处理电路等组成 ,其中光电处理电路全部由硬件实现。整个视觉传感系统可以避免焊接时弧光的干扰 ,实时、准确地检测出焊缝轨迹线偏差信号 ,具有实时性强、鲁棒性好、成本低、重量轻等优点。借助所研制的视觉传感器 ,球罐焊接机器人能够实现沿焊缝的自主运动和焊炬与焊缝的自动对中 ,满足球罐多层多道焊接工艺要求 ,实现球罐焊接作业的智能化、自动化     

基于BP神经网络的排爆机械臂逆运动学分析

机械臂逆运动学是已知末端执行器的位姿求解机械臂各关节变量,主要用于机械臂末端执行器的精确定位和轨迹规划,如何高效的求解机械臂运动学逆解是机械臂轨迹控制的难点。针对传统的机械臂逆运动学求解方法复杂且存在多解等问题,提出一种基于BP神经网络的机械臂逆运动学求解方法。以四自由度机械臂为研究对象,对其运动学原理进行分析,建立BP神经网络模型并对神经网络算法进行改进,最后使用MATLAB进行仿真验证。仿真结果表明：使用BP神经网络模型求解机械臂逆运动学问题设计过程简单,求解精度较高,一定程度上避免了传统方法的不足,是一种可行的机械臂逆运动学求解方法。     

基于大数据分析的移动对象轨迹预测方法

对移动对象的轨迹预测将在移动目标跟踪识别中具有较好的应用价值。移动对象轨迹预测的基础是移动目标运动参量的采集和估计,移动目标的运动参量信息特征规模较大,传统的单分量时间序列分析方法难以实现准确的参量估计和轨迹预测。提出一种基于大数据多传感信息融合跟踪的移动对象轨迹预测算法。首先进行移动目标对象进行轨迹跟踪的控制对象描述和约束参量分析,对轨迹预测的大规模运动参量信息进行信息融合和自正整定性控制,通过大数据分析方法实现对移动对象运动参量的准确估计和检测,由此指导移动对象轨迹的准确预测,提高预测精度。仿真结果表明,采用该算法进行移动对象的运动参量估计和轨迹预测的精度较高,自适应性能较强,稳健性较好,相关的指标性能优于传统方法。     

Trajectory Planning of Robot Manipulator Based on RBF Neural Network

Robot manipulator trajectory planning is one of the core robot technologies, and the design of controllers can improve the trajectory accuracy of manipulators. However, most of the controllers designed at this stage have not been able to effectively solve the nonlinearity and uncertainty problems of the high degree of freedom manipulators. In order to overcome these problems and improve the trajectory performance of the high degree of freedom manipulators, a manipulator trajectory planning method based on a radial basis function (RBF) neural network is proposed in this work. Firstly, a 6-DOF robot experimental platform was designed and built. Secondly, the overall manipulator trajectory planning framework was designed, which included manipulator kinematics and dynamics and a quintic polynomial interpolation algorithm. Then, an adaptive robust controller based on an RBF neural network was designed to deal with the nonlinearity and uncertainty problems, and Lyapunov theory was used to ensure the stability of the manipulator control system and the convergence of the tracking error. Finally, to test the method, a simulation and experiment were carried out. The simulation results showed that the proposed method improved the response and tracking performance to a certain extent, reduced the adjustment time and chattering, and ensured the smooth operation of the manipulator in the course of trajectory planning. The experimental results verified the effectiveness and feasibility of the method proposed in this paper.     

An Efficient Online Trajectory Generation Method Based on Kinodynamic Path Search and Trajectory Optimization for Human-Robot Interaction Safety

With the rapid development of robot perception and planning technology, robots are gradually getting rid of fixed fences and working closely with humans in shared workspaces. The safety of human-robot coexistence has become critical. Traditional motion planning methods perform poorly in dynamic environments where obstacles motion is highly uncertain. In this paper, we propose an efficient online trajectory generation method to help manipulator autonomous planning in dynamic environments. Our approach starts with an efficient kinodynamic path search algorithm that considers the links constraints and finds a safe and feasible initial trajectory with minimal control effort and time. To increase the clearance between the trajectory and obstacles and improve the smoothness, a trajectory optimization method using the B-spline convex hull property is adopted to minimize the penalty of collision cost, smoothness, and dynamical feasibility. To avoid the collisions between the links and obstacles and the collisions of the links themselves, a constraint-relaxed links collision avoidance method is developed by solving a quadratic programming problem. Compared with the existing state-of-the-art planning method for dynamic environments and advanced trajectory optimization method, our method can generate a smoother, collision-free trajectory in less time with a higher success rate. Detailed simulation comparison experiments, as well as real-world experiments, are reported to verify the effectiveness of our method.     

Reinforcement Learning-Based Reactive Obstacle Avoidance Method for Redundant Manipulators

Redundant manipulators are widely used in fields such as human-robot collaboration due to their good flexibility. To ensure efficiency and safety, the manipulator is required to avoid obstacles while tracking a desired trajectory in many tasks. Conventional methods for obstacle avoidance of redundant manipulators may encounter joint singularity or exceed joint position limits while tracking the desired trajectory. By integrating deep reinforcement learning into the gradient projection method, a reactive obstacle avoidance method for redundant manipulators is proposed. We establish a general DRL framework for obstacle avoidance, and then a reinforcement learning agent is applied to learn motion in the null space of the redundant manipulator Jacobian matrix. The reward function of reinforcement learning is redesigned to handle multiple constraints automatically. Specifically, the manipulability index is introduced into the reward function, and thus the manipulator can maintain high manipulability to avoid joint singularity while executing tasks. To show the effectiveness of the proposed method, the simulation of 4 degrees of planar manipulator freedom is given. Compared with the gradient projection method, the proposed method outperforms in a success rate of obstacles avoidance, average manipulability, and time efficiency.     

RBFNN结合自适应边界的机器人手臂轨迹跟踪控制系统设计

针对机器人手臂动态模型中存在动态不确定性问题,提出一种结合径向基函数神经网络(RBFNN)和自适应边界控制的机械臂轨迹跟踪方法。利用RBF神经网络在线学习系统中现有的结构化和非结构化不确定性,近似补偿未知动态部分;利用自适应边界来估计非结构化不确定性上的未知边界和神经网络重建误差;通过加权矩阵产生的李雅普诺夫函数证明了该系统具有渐进稳定性。利用三自由度机械臂进行实验,结果表明,相比其他几种较为先进的控制器,本文设计的控制器具有最优的控制精度。     

基于OSG的空间机械臂三维仿真平台的设计与实现

为了实现空间机械臂路径规划算法的可视化仿真,采用OSG(OpenSceneGraph)技术,开发了一个实用方便的空间机械臂三维仿真平台。该仿真平台在VS2005开发平台上,基于QT框架类和OSG的图形库进行开发,将仿真平台系统框架分为了OSG仿真界面,任务管理,数据管理和路径规划四个模块并设计了人机交互界面。最后,通过典型的仿真实验对仿真平台进行了测试,有效的验证了空间机械臂单臂路径规划算法和双臂协调路径规划算法的正确性以及空间机械臂三维仿真平台的可行性。     

Motion planning and actuator specialization in the control of active-flexible link robots

Trajectory planning is a well-known open-loop control strategy to minimize residual vibrations in point-to-point tasks of systems featuring mechanical flexibility. However, the major drawback of open-loop control is its limitation in coping with modeling uncertainty. In this paper a novel approach to trajectory planning based on LQR theory is proposed and applied to a single flexible link robot. To improve performance under parameter uncertainty the strategy is combined with collocated vibration control through piezoelectric actuation of the link. This combination raises the issue of the roles and the contribution of each actuator type to the overall performance of the maneuver. An actuator specialization is proposed where the joint controller is responsible for the gross vibrationless motion of the link, while the link actuators are expected to deal only with residual vibrations that may arise from modeling errors. Simulation and experimental results validate the trajectory planning methodology and the combination of the open-loop strategy with collocated vibration control.     

自动化控制下机械手臂运动轨迹研究

对机械手臂运动轨迹进行优化控制,能改善机械手臂的自动控制性能。为了提高机械臂的控制稳健性,提出一种基于变结构模糊PID控制的机械手臂运动轨迹优化控制模型。首先采用末端效应逆运动学模型构建机械手臂的运动规划约束参量数学模型,采用七自由度运动空间重构方法建立机械手臂运动的动力学方程。然后通过纵向定常运动,分析建立机械手臂整定控制目标函数,求解机械臂在抓取作业过程中的最佳导引控制律,采用变结构模糊PID控制方法进行运动轨迹的误差修正,实现机械臂自动控制优化。最后通过仿真实验进行控制性能测试,结果表明,采用该方法进行机械手臂运动轨迹控制的精度较高,对机械臂位形变化轨迹的预测准确性较好。