Optimal Robot Speed Trajectory by Minimization of the Actuator Motor Electromechanical Losses

This paper considers the control problem of a robotic manipulator with separately excited dc motor drives as actuators. An innovative method is proposed which achieves robot speed-control requirements, with simultaneous minimization of total electromechanical losses, while the drives follow the desired speed profiles of the robot joints under various loads and random load disturbances. If there is no demand for a specific speed profile, the optimal speed trajectory is determined by minimizing an electromechanical losses criterion. Controllable energy losses, such as armature copper losses, armature iron losses, field copper losses, stray load losses, brush load losses, friction and windage losses, can be expressed proportionally to the squares of the armature and the field (exciting) currents, the angular velocity and the magnetic field flux. The controllable energy loss term is also included in the optimal control integral quadratic performance index, defined for the whole operation period. Thus the appropriate control signals required for following the desired trajectory by simultaneous energy loss minimization for the whole operation interval are achieved. Two case studies of optimal robot control with and without minimization of actuator energy losses are presented and compared, showing the energy savings that can be achieved by the proposed methodology.     

A Scalable Intelligent Takeoff Controller for a Simulated Running Jointed Leg

Running with jointed legs poses a difficult control problem in robotics. Neural controllers are attractive because they allow the robot to adapt to changing environmental conditions. However, scalability is an issue with many neural controllers. This paper describes the development of a scalable neurofuzzy controller for the takeoff phase of the running stride. Scalability is achieved by selecting a controller whose size does not grow with the dimensionality of the problem. Empirical results show that with proper design the takeoff controller scales from a leg with a single movable link to one with three movable links without a corresponding growth in size and without a loss of accuracy.     

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。