一种改进的足球机器人射门算法

提出一种改进的射门算法.通过路径规划,使得机器人沿着平滑的轨迹将位姿调整到射门状态,然后,根据位姿变化最小的原则,从对方门线的坐标点中选择射门目标点,以圆弧路径完成射门过程.试验表明,算法可以提高射门成功率.     

时变机器人系统的重复学习控制: 一种混合学习方案

Repetitive learning control is presented for finite-time-trajectory tracking of uncertain time-varying robotic systems. A hybrid learning scheme is given to cope with the constant and time-varying unknowns in system dynamics, where the time functions are learned in an iterative learning way, without the aid of Taylor expression, while the conventional differential learning method is suggested for estimating the constant ones. It is distinct that the presented repetitive learning control avoids the requirement for initial repositioning at the beginning of each cycle, and the time-varying unknowns are not necessary to be periodic. It is shown that with the adoption of hybrid learning, the boundedness of state variables of the closed-loop system is guaranteed and the tracking error is ensured to converge to zero as iteration increases. The effectiveness of the proposed scheme is demonstrated through numerical simulation.     

基于广义双曲正切模型的机器人鲁棒模糊自适应控制

利用广义模糊双曲正切模型的全局逼近特点,设计一种模糊自适应控制器用于机器人轨迹跟踪控制.广义双曲正切模型利用输入变量的平移能以任意精度逼近系统的不确定动态.对于系统不确定外界干扰和模糊系统的逼近误差,通过求解一个线性矩阵不等式来保证闭环系统的鲁棒稳定性.对比传统的模糊基函数,在保证系统跟踪精度的前提下,双曲正切模糊基函数的自适应调整参数大大减少,仿真表明该控制算法具有较强的鲁棒性能和较好的跟踪性能.     

附加端子及其对智能机器人类型产品电磁兼容检测的适用性分析

讨论和分析了智能机器人类型产品进行电磁兼容检测的标准适用性问题。结合标准CISPR 14-1给出的限值和测试要求,描述了在电源端子和附加端子上进行传导骚扰测试的测量程序。分析了标准CISPR 14-1中对使用不同电源（供电网络供电,或者电池供电）要求的测试要求。使用某型号智能机器人产品分析了其附加端子的特征,讨论了如何对附加端子进行分类,并提供了对此类产品进行电磁兼容检测的规范流程。     

Neurobiology suggests the design of modular architectures for neural control

The existence of modular structures in the biological world strongly suggests that the training of this kind of structure is actually feasible. It is a key indication for the development of neural network applications, especially in the field of robotics. Indeed, a single network can only efficiently treat problems with few independent variables; the combination of several networks is necessary to address more complex tasks. We investigate learning techniques and show that using a particular form of architecture can ease the training of a modular structure: a bi-directional structure that allows combining several neural networks. The approach is illustrated with Kohonen's self-organizing maps for a robotic visual servoing task.     

两类仿鲹科机器鱼倒游运动控制方法的对比研究

给出并比较了两类分别采用鱼体波动方程和中枢模式发生器（Central pattern generator,CPG）控制仿鲹科机器鱼倒游运动的方法.前者主要通过修改鱼体波动方程、颠倒机器鱼各个关节的控制规律来实现 鱼体倒游;后者则基于CPG模型,产生各个关节的节律控制信号.基于CPG的倒游方法可进一步细分为两种:1） 相位颠倒的CPG控制方法,即通过逆转CPG控制机器鱼直游的相位关系;2） 相位-幅值颠倒的CPG控制方法,即通过逆转鱼体波的传播方向和摆动幅值来实现机器鱼倒游.文中针对这两大类、三种机器鱼倒游运动控制方法 进行了分析、仿真和实验.实验结果表明:在相同参数配置下,采用相位颠倒的CPG控制方法产生的倒游速度最大,但游动对水的扰动也最大;而采用鱼体波倒游和相位-幅值颠倒的CPG控制方法时,两者产生的最大倒游速度相差不大,扰动较小.此外,采用鱼体波倒游方法在频率切换时会有抖动现象,需要设计专门的过渡函数来消除;而采用CPG模型的方法 则可以实现平滑过渡.上述结果对提高水下游动机器人的机动性能具有重要的指导意义.     

基于任务空间的无标定视觉机械臂自适应跟踪控制

针对动力学参数不确定的无标定视觉机械臂系统,研究基于任务空间的自适应控制问题。对于控制器的设计,首先研究机械臂动力学参数不确定情况下基于任务空间的控制问题,然后设计自适应摄像机标定控制器,最后根据任务空间信息和图像空间信息的一致收敛关系统一两部分控制器,设计整个闭环系统控制信号和自适应控制律。实验结果表明了所提出的控制方法的有效性。     

Experimental control of a single-link flexible robot arm using energy shaping

Flexible-link robotic manipulators are mechanical devices whose control can be rather challenging, among other reasons because of their intrinsic under-actuated nature. This paper presents the application of an energy-based control design methodology (the so-called IDA-PBC, interconnection and damping assignment passivity-based control) to a single-link flexible robotic arm. It is shown that the method is well suited to handle this kind of under-actuated device not only from a theoretical viewpoint but also in practice. A Lyapunov analysis of the closed-loop system stability is given and the design performance is illustrated by means of a set of simulations and laboratory control experiments, comparing the results with those obtained using conventional control schemes for mechanical manipulators.     

Adaptive stiffness estimation for compliant robotic manipulation using stochastic disturbance models

To achieve haptic telepresence and proper contact behaviour, the control action of a robotic manipulator must be designed with respect to contact parameters. Unfortunately, it is hard to know these parameters exactly in unknown or partly known environments. In this case, contact instability and poor dynamic accuracy can arise due to the presence of modelling errors in the control design. To overcome these problems, online estimation of the relevant contact parameters can be performed, with corresponding adaptation of control laws. This article presents an algorithm for online stiffness estimation for compliant robotic manipulation based on the extended state-space representation of the system and force signals. No position or velocity measurements are required. The algorithm, supported by theoretical analysis, uses offline data concerning several stiffness mismatch scenarios and, through a least square error analysis, computes an estimate of the stiffness value. Simulation results are presented, with fast and accurate estimation even in the presence of noise, highlighting the merits of the method.     

Adaptive task-space synchronisation of networked robotic agents without task-space velocity measurements

In this paper, we investigate the problem of task-space synchronisation of multiple robotic agents in the presence of uncertain kinematics and dynamics. Our control objective is to realise synchronisation without the measurements of task-space velocity. The communication topology is assumed to be directed graphs containing a spanning tree. A decentralised task-space observer with kinematic parameter updating is proposed to avoid the reliance of task-space velocity. Based on the observer, we propose the distributed adaptive synchronisation controller for two cases: (1) the leaderless consensus case and (2) the leader-follower case, where all the followers track the convex hull spanned by the virtual leaders and for each follower, it is required that there exists at least one leader that has a directed path to the follower. The asymptotic synchronisation is proved with Lyapunov analysis and input–output stability analysis tools. Simulations with multiple robotic agents are performed to show the effectiveness of the proposed schemes.