Introducing autonomous aerial robots in industrial manufacturing

Although ground robots have been successfully used for many years in manufacturing, the capability of aerial robots to agilely navigate in the often sparse and static upper part of factories makes them suitable for performing tasks of interest in many industrial sectors. This paper presents the design, development, and validation of a fully autonomous aerial robotic system for manufacturing industries. It includes modules for accurate pose estimation without using a Global Navigation Satellite System (GNSS), autonomous navigation, radio-based localization, and obstacle avoidance, among others, providing a fully onboard solution capable of autonomously performing complex tasks in dynamic indoor environments in which all necessary sensors, electronics, and processing are on the robot. It was developed to fulfill two use cases relevant in many industries: light object logistics and missing tool search. The presented robotic system, functionalities, and use cases have been extensively validated with Technology Readiness Level 7 (TRL-7) in the Centro Bahía de Cádiz (CBC) Airbus D&S factory in fully working conditions.     

Safe and intuitive manual guidance of a robot manipulator using adaptive admittance control towards robot agility

Key areas of robot agility include methods that increase capability and flexibility of industrial robots and facilitate robot re-tasking. Manual guidance can achieve robot agility effectively, provided that a safe and smooth interaction is guaranteed when the user exerts an external force on the end effector. We approach this by designing an adaptive admittance law that can adjust its parameters to modify the robot compliance in critical areas of the workspace, such as near and on configuration singularities, joint limits, and workspace limits, for a smooth and safe operation. Experimental validation was done with two tests: a constraint activation test and a 3D shape tracing task. In the first one, we validate the proper response to constraints and in the second one, we compare the proposed approach with different admittance parameter tuning strategies using a drawing task where the user is asked to guide the robot to trace a 3D profile with an accuracy or speed directive and evaluate performance considering path length error and execution time as metrics, and a questionnaire for user perception. Results show that appropriate response to individual and simultaneous activation of the aforementioned constraints for a safe and intuitive manual guidance interaction is achieved and that the proposed parameter tuning strategy has better performance in terms of accuracy, execution time, and subjective evaluation of users.     

政务终端安全面临的问题与对策研究

文章首先对政务终端安全和CGDCC进行分析,其次剖析政务终端安全在部署实施、技术支撑、安全建设等方面面临的问题。最后提出从调度、验证、审计等方面,结合等级保护标准,强化政务终端安全的解决方案。     

基于非线性PID的柔性两轮机器人运动控制

柔性两轮机器人是一种不稳定、非线性、强耦合系统。该系统的突出特点是在机器人的腰部装有柔性的机体结构,能够更好地模拟人和动物的生物动力学特性,具有更好的仿生性质,同时,系统的控制难度显著增大,为使机器人能够平衡直立运动,且具有较强的鲁棒性,提出了非线性PD的姿态平衡控制方法,实现了机器人的姿态平衡,并同时设计了PID航向差动控制结构驱动左右轮电机,使机器人能够完成直线行进、自旋、环绕等多种运动平衡模式。实验结果表明,机器人具有优良的平衡能力和机动性能,从而验证了方法的有效性。     

基于机器人运动模型的EKF-SLAM算法改进

针对两轮驱动机器人运动模型定向误差的累积问题,提出改进的三轮驱动机器人运动模型,对EKF-SLAM算法的一致性进行改进;该模型通过对机器人车轮线速度的解耦运算,将机器人运动过程中的旋转角速度提取出来并作为系统的控制输入之一,从而可以直接得到各个控制时间间隔内的机器人姿态角变化,很好地避免了机器人定向误差的累积;最后,基于归一化估计方差的检验标准进行实验,验证了三轮驱动机器人运动模型有效提高了EKF-SLAM算法的一致性。     

以ARM为核心的嵌入式体感遥控器设计

介绍一种以ARM为核心的嵌入式服务机器人体感遥控器的设计。硬件上,本遥控器采用具有ARM Cortex—M3内核的STM32F103C8T6作为核心处理器,选用ST公司的iNEMO惯性导航模块进行手部姿态的识别,同时还具有LCD显示模块、无线收发模块和电源模块;软件上,采用嵌入式操作系统μC／OS—Ⅱ实现多任务的调度和外围设备的管理。经实验验证,本遥控器具有高稳定性、高实时性、高可靠性、低误码率等优点。     

Design of robotic visual servo control based on neural network and genetic algorithm

A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation (BP) neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP algorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.     

Systematic robustness analysis of least squares mobile robot velocity estimation using a regular polygonal optical mouse array

This paper presents the robust velocity estimation of an omnidirectional mobile robot using a regular polygonal array of optical mice that are installed at the bottom of a mobile robot. First, the velocity kinematics from a mobile robot to an array of optical mice is derived, from which the least squares estimation of the mobile robot velocity is obtained as the simple average of the optical mouse velocity readings. Second, it is shown that a redundant number of optical mice contributes to the robustness of the least squares mobile robot velocity estimation against both measurement noises and partial malfunction of optical mice. Third, the sensitivity analysis of the least squares mobile robot velocity estimation to imprecise installation of optical mice is made, from which a practical method of optical mouse position calibration is devised. Finally, some experimental results using commercial optical mice are given to demonstrate the validity and performance of the proposed mobile robot velocity estimation. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

未知环境下机器人障碍物检测技术

未知环境下地面的不平坦性和机器人相对障碍物位姿的不确定性会造成障碍物特征提取困难,为了准确检测障碍物特征,采用3维相机获取机器人周围环境的灰度图像和距离信息。在此基础上,提出基于灰度信息和3维信息的"阈值法"进行障碍物区域的提取,并针对3维信息"阈值法"剔除的地面与障碍物过渡区域过多,以及机器人相对斜坡方位的不确定性引起的障碍物特征检测不准确,提出区域的恢复算法和表面法线坡度计算。实验结果表明,所提出的算法具有简单、有效、准确和鲁棒性强的优点。     

霍夫空间中多足球机器人协作目标定位算法

针对嵌入式仿人足球机器人提出一种霍夫空间中的多机器人协作目标定位算法。机器人利用实验场地中的标志物采用基于三角几何定位方法进行自定位,把机器人多连杆模型进行简化,通过坐标系位姿变换把图像坐标系转换到世界坐标系中,实现机器人目标定位;在多机器人之间建立ZigBee无线传感器网络进行通信,把多个机器人定位的坐标点进行霍夫变换,在霍夫空间中进行最小二乘法线性拟合,获取最优参数,然后融合改进后的粒子滤波实现对目标小球的跟踪;最后在21自由度的仿人足球机器人上进行仿真和实验。数据结果表明,这种多机器人协作的定位算法的精度提高了约48%,在满足实时性的前提下,对目标的跟踪效果也得到了改善。