基于广域网的遥操作工程机器人神经网络控制

针对在广域网环境下因较大网络时延造成遥操作工程机器人系统操作性能下降甚至系统不稳定的问题,提出一种神经网络控制方法。借助于广域网模拟器,在局域网环境下进行了不同网络时延下的位置阶跃响应和稳态跟踪实验研究。结果表明:与常规PID控制方法相比,该方法具有更好的动态和稳态特性,对网络时延具有较好的适应性和鲁棒性。研究结果对提高广域网环境下的遥操作工程机器人系统的操作性能具有指导意义。     

Optimal robot positioning using task-dependent and direction-selective performance indexes: General definitions and application to a parallel robot

Performance evaluation is an important issue for optimal robot positioning within workcells. Performance indexes can provide essential contributions to such an evaluation, in particular if they can account for the specific task with respect to which the optimization is carried out.     

A cognitive robot architecture based on tactile and visual information

In this paper, we propose an architecture for a cognitive robot based on tactile and visual information. Visual information contains various features such as location and area of various colored regions. Most of these features are irrelevant for object recognition to achieve the given task. In the architecture, tactile information plays a key role in the selection of visual features and discritization of selected features. In order to find appropriate visual features we use a correlation coefficient between the values of the features and action series. Then the ChiMerge algorithm is employed to discritize the value of the selected feature into a small number of intervals. Consequently, quantization of a state space to accomplish the given task is achieved. An appropriate behavior to the given task is acquired by using this state space with reinforcement learning algorithm. We give experimental results of computer simulation to show the validity of our method.     

Transition Motion from Ladder Climbing to Brachiation with Optimal Load-Allocation Control

Abstract

This paper describes the transition motion from ladder climbing to brachiation for a multi-locomotion robot (MLR). The MLR has versatile modes of locomotion, such as biped walking, quadruped walking, brachiation and ladder climbing. The transition is a challenging motion, because the environmental boundaries change and the robot has to switch the form of its locomotion depending on its surroundings, situations and purposes. The robot supports itself with three end-effectors that maintain its stability, while one hand transfers from a rung on the vertical ladder to a new rung behind the robot for brachiation. A closed kinematic chain is formed by the robot links and the ladder. In this case, if the number of position-controlled active joints is greater than the number of the chain’s degrees of freedom, an internal stress appears because of unavoidable position errors. The huge internal stress may lead some motors to become overloaded. Since the safety of each motor is very important for a serial-link robot, a load-allocation algorithm is proposed to balance the loads of the joint motors. The algorithm is verified through experiments.     

On rotations and translations with application to robot manipulators

Robot motion is described by a set of positions and orientations of the robot's end-effector relative to some base coordinate system. Different methods to describe this motion are available and most of them are presented in this paper. Methods for position vector, free vector, and line vector transformation are presented and compared, and the advantages and disadvantages, the simplicity, and the number of arithmetic operations required of the different methods are addressed. An example of the application of these methods to a six degree-of-freedom robot is given.     

Iterative Learning Control Algorithm with a Fixed Step

Iterative Learning Control (ILC) captures interests of many scholars because of its capability of high precision control implement without identifying plant mathematical models, and it is widely applied in control engineering. Presently, most ILC algorithms still follow the original ideas of ARIMOTO, in which the iterative-learning-rate is composed by the control error with its derivative and integral values. This kind of algorithms will result in inevitable problems such as huge computation, big storage capacity for algorithm data, and also weak robust. In order to resolve these problems, an improved iterative learning control algorithm with fixed step is proposed here which breaks the primary thought of ARIMOTO. In this algorithm, the control step is set only according to the value of the control error, which could enormously reduce the computation and storage size demanded, also improve the robust of the algorithm by not using the differential coefficient of the iterative learning error. In this paper, the convergence conditions of this proposed fixed step iterative learning algorithm is theoretically analyzed and testified. Then the algorithm is tested through simulation researches on a time-variant object with randomly set disturbance through calculation of step threshold value, algorithm robustness testing,and evaluation of the relation between convergence speed and step size. Finally the algorithm is validated on a valve-serving-cylinder system of a joint robot with time-variant parameters. Experiment results demonstrate the stability of the algorithm and also the relationship between step value and convergence rate. Both simulation and experiment testify the feasibility and validity of the new algorithm proposed here. And it is worth to noticing that this algorithm is simple but with strong robust after improvements, which provides new ideas to the research of iterative learning control algorithms.     

基于深度学习的采摘机器人目标识别定位算法

为了提升采摘机器人对果实的识别准确率以及定位定精度,提出一种基于深度学习Faster-RCNN框架的采摘机器人目标识别和定位算法.首先采用卷积神经网络VGG16模型提取输入图像的特性信息,并利用区域提议网络RPN生成含有目标的候选框,通过引入自适应候选框数的方法有效提升了算法性能,然后利用多任务损失函数对目标进行分类识...     

悬挂式接管焊接机器人机电系统

针对接管相贯线处的焊接特点,研发了悬挂式接管焊接机器人,介绍了机械结构特点和适用性.控制系统采用工业PC作为主控计算机和PMAC多轴控制卡进行多轴控制,利用二级控制结构实现作业管理,协调各轴运动完成焊接作业.进行了在筒体上外接管和内接管的焊接试验与在椭球体上外接管与内接管的焊接试验.结果表明,机器人的机械本体结构和控制系统能够实现多种接管的焊接需求,能够很好地完成接管相贯线处的焊接,提高了工作效率和焊接质量.     

教学多功能机器人的设计与实现

机器人作为电子学、机械学、计算机技术、人工智能等学科的典型应用被广泛地用来作为高校实践课与第二课堂的典型载体。本文多功能机器人采用力矩直流电机驱动,大大降低机器人的造价成本,为工科电类专业单片机、机电一体化、智能电子技术实验、实训教学提供了很好的手段,具有造价低,调控容易、重复性好、配智能电路控制模块,功能无限扩展,技术先进等特点。     

Shared human–robot path following control of an unmanned ground vehicle

This paper considers the shared path following control of an unmanned ground vehicle by a single person. A passive measure of human intent is used to blend the human and machine inputs in a mixed initiative approach. The blending law is combined with saturated super-twisting sliding mode speed and heading controllers, so that exogenous disturbances can be counteracted via equivalent control. It is proven that when the proposed blending law is used, the combined control signals from both the human and automatic controller respect the actuator magnitude constraints of the machine. To demonstrate the approach, shared control experiments are performed using an unmanned ground vehicle, which follows a lawn mower pattern shaped path.