利用协调控制法回避机械手的奇异位形

本文考虑到目前回避６自由度机器人之奇异位形的方法在控制上的不足，将陆震先生１９９０年提出的协调控制法加以推广，该方法能充分利用不定位形的特点回避奇异位形，可以较有效地用于６自由度机器人的控制而不会发生关节速度超限和手部运动偏差，是目前一种较理想的回避奇异方法。     

基于区域限定的奇异位置避免规划算法

目前人们关于奇异位形的处理研究主要包括两大类,一类是研究如何避免,一类是研究如何通过奇异点.在分析了国内外关于奇异位形的研究基础上,本文提出了基于空间区域限定的奇异位置避免算法.其核心思想就是预先对机器人运动轨迹进行规划,给出了奇异位置及邻近奇异位置的区域划分方法,从而保证在笛卡尔空间规划时能规划出一合理的插值点,同时也基于高次多项式曲线理论对关节空间规划做了优化,保证了关节和末端运动的连续性、稳定性等.通过6轴机械臂在四五六关节时的奇异为实例,运用该算法对奇异的处理做了实例分析.然后通过给定初始点和目标点的位姿等参数,定时采样数据,并利用MATLAB对规划前后获得的数据进行了图形仿真,验证了该算法的正确性和可行性.     

并联机构不同正解间无奇异转换问题探讨

并联机构的正解具有多解性,以一种平面三自由度并联机构为例,研究了不同正解之间的无奇异连接路径问题．结合Innocenti发现的第一条无奇异路径,采用基于奇异曲面的图形化方法分析了正解构型在工作空间中的分布．发现了两个正解间的多条类似路径,这些路径形成了连接两个正解位形的近似于螺旋状的管道空间．首次发现了在其它的正解之间也存在着这样的非奇异路径．这些结果表明并联机构的奇异曲面及正解分布异常复杂,如果两个正解对应的雅可比矩阵行列式值异号,则一定不存在无奇异路径;如果同号,则还要根据奇异曲面来定．两个正解构型间无奇异路径的判定还最终依赖于对奇异曲面更为清楚的描述．     

机器人操作臂奇异路径约束最优轨迹规划

路径约束最优轨迹规划的关键是引入标量路径参数来降低优化问题的维数 ．当路径穿越奇异点时，由于关节位移难以表示为任务空间路径参数的解析函数，给常规的 路径参数化方法带来困难．本文引入一种新的参数化方法，采用路径跟踪方程解曲线的弧长 为参数，解决了奇异点邻域的路径跟踪问题，把奇异路径轨迹规划转化为常规规划问题，并 采用动态规划方法求解轨迹规划问题．仿真表明，本文提出的参数化方法与动态规划结合起 来，是解决奇异路径最优轨迹规划的有效途径．      

一种新的指纹奇异点区增强算法

提出了一种两步增强指纹奇异点区的新方法。使用基于瑞利函数的滤波器对奇异点区进行带通滤波,使用间隔22.5˚的8方向加博滤波器组对该区域进行增强,在获得的8幅滤波图像上,通过计算质量指标,得到对应于16个方向子区的16幅最优子区图像,合成这些子区图像,得到最终的奇异点区增强结果。实验结果表明该方法有效增强了指纹的奇异点区。     

自由漂浮空间机器人回避动力学奇异的轨迹规划

针对非完整约束导致的自由漂浮空间机器人广义雅可比矩阵动力学奇异性问题,提出一种间接求解机器人逆运动学的方案.该方案通过运动方程分解并构造迭代函数,将动力学奇异转换为运动学奇异问题,避免直接求解逆广义雅可比矩阵,解决广义雅可比矩阵动力学参数相关特性问题,仿真结果表明该方法能够有效地实现自由漂浮空间机器人回避动力学奇异的非完整轨迹规划.     

机器人奇异位形控制方法的研究

本文针对机器人运动学反解的一般分析方法进行了介绍，并指出了各自的优缺点，最后指出了机器人奇异位形的研究热点。     

一种局域网互连拥塞回避新算法

在通过高速主干网互连局域网时，由于速率不匹配，在目的局域网处会造成拥塞和数据丢失。本文提出了一种同时采用开环和闭环控制，结合许可证控制和时间戳调度策略，以FCFS方式服务的拥塞回避新算法。仿真结果表明，本文提出的新算法优于以往算法。     

基于遗传算法的足球机器人比赛中障碍回避策略的设计

本文介绍了基于遗传算法的足球机器人系统中障碍回避策略的设计,使机器人能避 开障碍物从给定点到目标点找到一条比较短的路径,并阐述了具体算法的设计与实现,并给 出了仿真结果．     

An Artificial Neural Network Approach for Inverse Kinematics Computation and Singularities Prevention of Redundant Manipulators

In this article an Artificial Neural Network (ANN) approach for fast inverse kinematics computation and effective singularities prevention of redundant robot manipulators is presented. The approach is based on establishing some characterizing matrices, representing some geometrical concepts, in order to yield a simple performance index and a null space vector for singularities avoidance/prevention and safe path generation. Here, this null space vector is computed using a properly trained ANN and included in the computation of the inverse kinematics being performed also by another properly trained ANN.     

A real-time impedance-based singularity and joint-limits avoidance approach for manual guidance of industrial robots

This paper studies real-time manual guidance considering singularity and joint-limits avoidance using impedance control in an industrial scenario. The operator is responsible for keeping the end-effector (EE) away from the robot’s singularity and joint-limits. The proposed approach detects the singularity and joint-limits in real-time. Then, virtual stiffness and damping are added to target stiffness and damping as the robot is getting close to the singularity or joint-limit. A criterion is presented for detection of singularity by combining manipulability ellipsoid and condition number. Also a new joint to Cartesian space transformation is formulated in order to convert joint stiffness and damping to Cartesian stiffness and damping for joint-limits avoidance method. The presented approach is applied on a SCARA robot. An experiment is performed in this paper to investigate singularity and joint-limits avoidance separately as well as together. Increase in stiffness and damping warn the operator of the possibility of singularity or joint-limits allowing the operator to changes the EE path. The proposed approach, eliminates the need for a robotics expert by allowing any operator with no knowledge about robot singularity and joint-limits to interact and teach the robot in a safe, real-time and time-saving manner.     

A Novel Navigation Method for Autonomous Mobile Vehicles

This paper presents a novel navigation method for Autonomous Mobile Vehicle in unknown environments. The proposed navigator consists of an Obstacle Avoider (OA), a Goal Seeker (GS), a Navigation Supervisor (NS) and an Environment Evaluator (EE). The fuzzy actions inferred by the OA and the GS are weighted by the NS using the local and global environmental information and fused through fuzzy set operation to produce a command action, from which the final crisp action is determined by defuzzification. The EE tunes the supports of the fuzzy sets for the OA and the NS; therefore, the capability of the navigation method is enhanced. Simulation shows that the navigator is able to perform successful navigation task in various unknown or partially known environments, and it has satisfactory ability in tackling moving obstacles. More importantly, it has smooth action and exceptionally good robustness to sensor noise.     

A Novel Approach for Mobile Robot Navigation with Dynamic Obstacles Avoidance

This paper proposes a new approach for trajectory optimization of a mobile robot in a general dynamic environment. The new method combines the static and dynamic modes of trajectory planning to provide an algorithm that gives fast and optimal solutions for static environments, and generates a new path when an unexpected situation occurs. The particularity of the method is in the representation of the static environment in a judicious way facilitating the path planning and reducing the processing time. Moreover, when an unexpected obstacle blocks the robot trajectory, the method uses the robot sensors to detect the obstacle, finds a best way to circumvent it and then resumes its path toward the desired destination. Experimental results showed the effectiveness of the proposed approach.     

基于失败连接流量偏离度的蠕虫早期检测方法

通过分析网络蠕虫攻击的特点，定义了能够反映蠕虫攻击特征的失败连接流量偏离度（FCFD）的概念，并提出了一种基于FCFD时间序列分析的蠕虫早期检测方法。该方法利用小波变换对FCFD时间序列进行多尺度分析，利用高频分量模极大值进行奇异点检测，从而发现可能的蠕虫攻击。同时给出了一种基于失败连接分析的蠕虫感染主机定位和蠕虫扫描特征提取方法。实验结果显示，该方法能够有效检测未知蠕虫的攻击。和已有方法相比，该方法具有更高的检测效率和更低的误报率。     

Study on the Configuration Space Based Algorithmic Path Planning of Industrial Robots in an Unstructured Congested Three-Dimensional Space: An Approach Using Visibility Map

Obstacle avoidance and subsequently collision-free path planning is a potential field of robotics research, specially in the perspective of today's industrial scenario. In this paper, the celebrated method, namely, Visibility Map is being used to generate feasible collision-free near-optimal safe path(s) for a three- dimensional congested robot workspace using heuristic algorithms. The final path is obtainable in terms of joint configurations, by considering the Configuration Space of the task-space. The developed algorithms have been verified by considering typical 2D workspaces at the onset, cluttered with different obstacles (convex and/or concave) with regular geometries and later on, with the real spatial manifold. The outcome of these algorithms has been found instrumental in programming an industrial robot in order to perform a series of task in the shop-floor. A case-study reveals the effectiveness of the heuristics involved in the developed algorithms, by virtue of the successful application in an unstructured industrial environment to carry out robotized material handling operation in real-time.     

Self-Organizing Feature Maps for Modeling and Control of Robotic Manipulators

This paper presents a review of self-organizing feature maps (SOFMs), in particular, those based on the Kohonen algorithm, applied to adaptive modeling and control of robotic manipulators. Through a number of references we show how SOFMs can learn nonlinear input–output mappings needed to control robotic manipulators, thereby coping with important robotic issues such as the excess degrees of freedom, computation of inverse kinematics and dynamics, hand–eye coordination, path-planning, obstacle avoidance, and compliant motion. We conclude the paper arguing that SOFMs can be a much simpler, feasible alternative to MLP and RBF networks for function approximation and for the design of neurocontrollers. Comparison with other supervised/unsupervised approaches and directions for further work on the field are also provided.     

A Dynamic-compensation Approach to Impedance Control of Robot Manipulators

This paper presents an impedance–control strategy with dynamic compensation for interaction control of robot manipulators. The proposed impedance controller has been developed considering that the equilibrium point of the closed-loop system, composed by the combination of the controller and the full nonlinear robot dynamics is, locally, asymptotically stable in agreement with Lyapunov’s direct method. The performance of the proposed controller is verified through simulation and experimental results obtained from the implementation of an interaction task involving a two degree-of-freedom, direct-drive robot.     

基于改进Dijkstra算法的机器人路径规划方法

本文提出一种利用栅格法和改进的Dijkstra算法进行机器人路径规划的方法。该方法利用栅格法对机器人的工作环境进行表示,利用改进的Dijkstra算法进行最短路径的搜索。应用该方法在对环境细化到包含10000个栅格节点的情况下，在主频1．7GHZ的计算机上规划路径的时间最长不超过0．3秒。实践证明该方法具有实时性和路径最优性。     

基于改进Dijkstra算法的机器人路径规划方法

本文提出一种利用栅格法和改进的Dijkstra算法进行机器人路径规划的方法。该方法利用栅格法对机器人的工作环境进行表示,利用改进的Dijkstra算法进行最短路径的搜索。应用该方法在对环境细化到包含10000个栅格节点的情况下,在主频1.7GHZ的计算机上规划路径的时间最长不超过0.3秒。实践证明该方法具有实时性和路径最优性。