手眼视觉系统变换关系的研究

手眼视觉系统是一类重要机器人视觉系统，在实现视觉实时跟踪控制过程中具有重要的作用．对手眼视觉系统的几何变换关系和微分变换关系进行了分析．基于这些变换关系，实现了手眼视觉系统跟踪平面物体匀速运动和转动的实验．     

Vehicle-command center communications in a robotic vehicle system

The U.S. Army Laboratory Command is developing a testbed for cooperative, real-lime control of multiple land vehicles from a remotely located command center. The system requires the development and integration of a variety of elements which allow the vehicles to perform autonomously and under supervisory and teleoperated control. The National Institute of Standards and Technology is supporting this program by designing the overall system control architecture based on experience gained in developing hierarchial control systems in robotics and automated manufacturing. This paper analyzes the characteristics of the communication link between the vehicle and the remote command center. Areas addressed include the communication technology, the information content and required rates, the control system communication requirements, communications support of the development effort and examination of available standards.     

An Advanced Telereflexive Tactical Response Robot

ROBART III is intended as an advanced demonstration platform for non-lethal tactical response, extending the concepts of reflexive teleoperation into the realm of coordinated weapons control (i.e., sensor-aided control of mobility, camera, and weapon functions) in law enforcement and urban warfare scenarios. A rich mix of ultrasonic and optical proximity and range sensors facilitates remote operation in unstructured and unexplored buildings with minimal operator oversight. Supervised autonomous navigation and mapping of interior spaces is significantly enhanced by an innovative algorithm which exploits the fact that the majority of man-made structures are characterized by (but not limited to) parallel and orthogonal walls. This paper presents a brief overview of the advanced telereflexive man-machine interface and its associated human-centered mapping strategy.     

Control of a Robotic Manipulator Using Artificial Neural Networks with On-line Adaptation

An adaptive neural system for positioning control of a PUMA 560 manipulator is presented". The computed torque method was implemented with a Multi-Layer Perceptron with on-line learning. The control scheme is implemented into two phases. The first one is the off-line phase in which the neural network is trained with previously known control actions. The second one is the on-line phase in which the neural network parameters are adapted while controlling the manipulator. The control system is able to respond to changes in the manipulator model and to load disturbances. As will be shown, control system performance is improved with the on-line learning strategy presented in this paper.     

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.