机器人轮椅用户行为与自主导航动态共享控制方法

机器人轮椅人机交互研究表明长时间采用单一模式交互容易导致用户操作意图误判且稳定性会变差,完全自主模式亦会因用户缺乏控制体验而产生沮丧情绪。针对当前基于人机协作的机器人轮椅交互存在模式间硬切换与缺乏对环境变化的动态调整能力的问题,本文以手势交互控制轮椅为基础,提出一种基于用户行为与自主导航相结合的机器人轮椅动态共享控制方法。首先基于Leap Motion传感器追踪用户掌心坐标,生成用户手势速度指令;其次,基于RPLIDAR A1激光雷达传感器并结合自主导航算法,生成自主导航控制指令;最后基于距离、疲劳及误差等多种约束条件实时更新人-机控制指令权重,实现对机器人轮椅的动态共享控制。实验结果表明,本文所提动态共享控制方法能根据轮椅运行环境与用户操作性能动态调整不同模式间的角色分配,避免了不同模式间的直接硬切换,具有较好的用户体验。     

Robot vision with cellular neural networks: a practical implementation of new algorithms

Cellular neural networks (CNNs) are well suited for image processing due to the possibility of a parallel computation. In this paper, we present two algorithms for tracking and obstacle avoidance using CNNs. Furthermore, we show the implementation of an autonomous robot guided using only real‐time visual feedback; the image processing is performed entirely by a CNN system embedded in a digital signal processor (DSP). We successfully tested the two algorithms on this robot. Copyright © 2006 John Wiley & Sons, Ltd.     

变电站二次设备巡检的Mecanum轮式机器人精确定位与作业辨识

通过巡检机器人进行变电站二次设备的监测是提升电力设备自动化、智能化管理的重要方式,有利于保障电力工程设备的安全运行。本研究开发了一种用于变电站二次设备自动化巡检的Mecanum轮式机器人,具备自主导航定位与作业辨识的能力,可极大提升设备巡检效率及保护压板状态识别准确性。通过Mecanum轮的驱动方式实现巡检机器人在狭窄作业环境下的灵活运动与姿态调整,多轨道升降平台实现对350-1800 mm高度范围内的二次设备及压板的图像采集与状态辨识。机器人采用基于激光雷达的SLAM导航方法进行自主定位导航,并结合基于视觉的路径提取与跟踪算法进行姿态位置修正,实现在待测点位置的精确定位。同时,提出了基于颜色辨识的图像排列与状态辨识方法,针对二次设备保护压板连通状态进行识别和判断。实验结果表明,研制的变电站二次设备巡检机器人可以实现自主导航与位置精确定位,在路径跟踪过程中最大偏角和偏距分别为±3°和±8 mm。结合机器视觉与颜色辨识的压板辨识方法可以准确识别压板状态,识别准确率大于95.80%,有助于提升机器人自动化的电力巡检作业水平。     

Analogic CNN algorithm for estimating position and size of moving objects

An analogic CNN algorithm is proposed for detection of multiple moving objects in high resolution, grey‐scale images taken from a fixed camera. The algorithm, based on simple 3 × 3 templates, can be implemented using CNN hardware, providing the real‐time operation required in surveillance and traffic control applications. Efficient separation of moving objects from the background is obtained through automatic threshold selection. The performance of the proposed method is shown using real‐life indoor and outdoor video sequences. Copyright © 2004 John Wiley & Sons, Ltd.     

Multi‐template approach to realize central pattern generators for artificial locomotion control

Biologically inspired control of artificial locomotion often makes use of the concept of central pattern generator (CPG), a network of neurons establishing the locomotion pattern within a lattice of neural activity. In this paper a new approach, based on cellular neural networks (CNNs), for the design of CPGs is presented. From a biological point of view this new approach includes an approximated chemical synapse realized and implemented in a CNN structure. This allows to extend the results, previously obtained with a reaction‐diffusion‐CNN (RD‐CNN) for the locomotion control of a hexapod robot, to a more general class of artificial CPGs in which the desired locomotion pattern and the switching among patterns are realized by means of a spatio‐temporal algorithm implemented in the same CNN structure. Copyright © 2002 John Wiley & Sons, Ltd.     

高压巡线机器人电磁导航系统研究与设计

为提高架空高压线路故障检测效率,研究并实现了高压巡线机器人自主巡检作业新方法,即巡线机器人在PC104硬件系统和嵌入式软件系统平台上分析处理输电线图像数据对其进行故障检测。基于电磁检测的导航系统由横竖两方向多方位的电磁传感器阵列组成;PC104采用相对值检测方法,根据高压输电线路周围磁场的感应电压跟半径的反比例关系原理,比较传感器阵列输出的系列模拟电压值来判断机器人相对输电线路的姿势并识别线上障碍;针对电磁导航系统信号特点,研究MATLAB数字滤波器优化设计方法;设计出IIR滤波器对经过放大的信号进行处理,研究并实现了PC104的IIR优化算法。仿真结果和现场试验证明,基于IIR滤波的巡线机器人电磁导航系统结构简单、效果显著。     

Watermarking on CNN‐UM for image and video authentication

In this paper a new approach to fragile watermarking technique is introduced. This problem is particularly interesting in the field of modern multimedia applications, when image and video authentication are required. The approach exploits the cellular automata suitability to work as pseudorandom pattern generators and extends the related algorithms under the framework of the cellular non‐linear networks (CNNs). The result is a novel way to perform watermarking generation in real time, using the presently available CNN‐universal chip prototypes. In this paper, both the CNN algorithms for fragile watermarking as well as on‐chip experimental results are reported, confirming the suitability of CNNs to successfully act as real‐time watermarking generators. The availability of CNN‐based visual microprocessors allows to have powerful algorithms to watermark in real time images or videos for efficient smart camera applications. Copyright © 2004 John Wiley & Sons, Ltd.     

Automatic detection and tracking of moving image target with CNN‐UM via target probability fusion of multiple features

A high speed target detection and tracking algorithm for a CNN‐UM chip is presented in this paper. The target confidence value is computed based on the fusion of target existence probabilities of features using products of weighted sums. The target decision is done with such a confidence value and target initiation is done through the temporal accumulation of the confidence. The probability of the target existence for each feature is created in the region of influence depending on the reliability and the strength of the feature. By virtue of the analogic parallel processing structure of the CNN‐UM (Roska T, Chua LO. The CNN universal machine: an analogic array computer. IEEE Trans. Circuits Systems II 1993; CAS‐40 : 163–173), real time tracking can be achieved with presently available technologies with the speed of several kilo‐frames per second. Due to the utilization of multiple features of target, robust target detection is possible via the proposed algorithm. On‐chip experiments of the proposed target‐tracking algorithm have been done and properties of the proposed approach are disclosed through the various experiments. Copyright © 2003 John Wiley & Sons, Ltd.     

Visual Avoidance of Collision with Randomly Moving Obstacles through Approximate Reinforcement Learning

In this research work, a hierarchical controller has been designed for an autonomous navigation robot to avoid unexpected moving obstacles where the state and action spaces are continuous. The proposed scheme consists of two parts: 1) a controller with a high-level approximate reinforcement learning (ARL) technique for choosing an optimal trajectory in autonomous navigation; and 2) a low-level, appearance-based visual servoing (ABVS) controller which controls and execute the motion of the robot. A novel approach for path planning and visual servoing has been proposed by the combined system framework. The characteristics of the on-board camera which is equipped on the robot is naturally suitable for conducting the reinforcement learning algorithm. Regarding the ARL controller, the computational overhead is quite low thanks to the fact that a knowledge of obstacle motion is not necessary. The developed scheme has been implemented and validated in a simulation system of obstacle avoidance. It is noted that findings of the proposed method are successfully verified by obtaining an optimal robotic plan motion strategy.     

融合行人运动信息的室内移动机器人动态避障方法

为了提高移动机器人在室内人机共融环境下的运动安全和交互性,提出了一种融合行人运动信息的室内移动机器人动 态避障方法,同时考虑任务约束和社会规则。 首先,利用 YOLO v3 算法和 Deep Sort 算法分别对室内环境中的行人进行实时检 测与目标跟踪,计算行人在过去时刻的历史轨迹。 然后,利用 Social-GAN 算法构建行人交互模型,实现轨迹预测。 在此基础上, 将行人的运动状态融合进机器人避障算法之中,根据社会规则设计评价函数,对机器人采样速度样本进行评估,使移动机器人 能够以安全和舒适的方式绕过行人,确保室内人机共融环境下移动机器人的社会接受性。 通过实验对比分析,与传统 DWA 方 法相比,本文方法不仅可以提高机器人导航避障效率,在相同室内场景下导航避障时间由 23. 56 s 提高到 19. 38 s,而且可以有 效降低与行人发生碰撞的风险,保证机器人导航的安全和社交性。     

3D Scan matching for mobile robot localization over rough terrain

In order to enable an autonomous mobile robot to travel over rough terrain, it necessitates the capability to detect self‐position accurately even when the odometry errors are increased in traveling. The conventional method can keep high speed and precise localization using iterative closest point algorithms or feature matching techniques. However, effects of steep changes of a mobile robot position are not considered when it travels over rough terrain. In this article, we propose the method for efficient real‐time 6D pose tracking using a rotating 2D laser scanner in traveling over rough terrain. For adaptation to steep changes of the position, weighted point clouds are generated based on the angular and the linear velocity measured by sensors mounted on the robot. And the position and posture of the robot are sequentially optimized by the scan matching in increments of 10 scans. In indoor experiments, we evaluated accuracy of our method when the robot passes on rugged floor. As a result, our method was performed with less than 0.078 m RMS positional error in real time.     

An IMM algorithm with federated information mode‐matched filters for AGV

In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) is presented. The developed navigation algorithm is an interacting multiple‐model (IMM) algorithm used to detect other AGVs using fused information from multiple sensors. In order to detect other AGVs, two kinematic models were derived: A constant‐velocity model for linear motion, and a constant‐speed turn model for curvilinear motion. In the constant‐speed turn model, a nonlinear information filter (IF) is used in place of the extended Kalman filter (KF). Being equivalent to the KF algebraically, the IF is extended to N‐sensor distributed dynamic systems. The model‐matched filter used in multi‐sensor environments takes the form of a federated nonlinear IF. In multi‐sensor environments, the information‐based filter is easier to decentralize, initialize, and fuse than a KF‐based filter. In this paper, the structural features and information‐sharing principle of the federated IF are discussed. The performance of the suggested algorithm using a Monte Carlo simulation is evaluated under the three navigation patterns. Copyright © 2006 John Wiley & Sons, Ltd.     

Pixel‐level snakes on the CNNUM: algorithm design,on‐chip implementation and applications

In this paper, a new algorithm for the cellular active contour technique called pixel‐level snakes is proposed. The motivation is twofold: on the one hand, a higher efficiency and flexibility in the contour evolution towards the boundaries of interest are pursued. On the other hand, a higher performance and suitability for its hardware implementation onto a cellular neural network (CNN) chip‐set architecture are also required. Based on the analysis of previous schemes the contour evolution is improved and a new approach to manage the topological transformations is incorporated. Furthermore, new capabilities in the contour guiding are introduced by the incorporation of inflating/deflating terms based on the balloon forces for the parametric active contours. The entire algorithm has been implemented on a CNN universal machine (CNNUM) chip set architecture for which the results of the time performance measurements are also given. To illustrate the validity and efficiency of the new scheme several examples are discussed including real applications from medical imaging. Copyright © 2005 John Wiley & Sons, Ltd.     

公路视觉导航中基于卡尔曼滤波器的3D运动参数估计

本文通过对室外行驶车辆上的CCD摄像机所采集的长序列立体图像的处理与分析 ,研究基于卡尔曼滤波器的三维 (3D)运动参数估计方法 ,以实现公路视觉导航中车道线的自动检测与跟踪。本文还阐述了一种扩展的卡尔曼滤波算法     

变电站设备巡检机器人视觉导航方法

针对变电站巡检工作的实际需求,介绍了一种基于轨线引导的巡检机器人单目视觉导航方法。对于预先设置的引导轨线和停靠位标识,采用OpenCV和DirectShow软件库来开发视频采集程序,实现道路视频信息的实时采集;通过HSI模型对图像进行颜色提取,再采用数学形态学处理去除干扰信息;最终采用统计8-连通区的方法将导航线和停靠位标识分割提取出来,用采样估算方法计算导航线参数,通过比例系数融合导航参数以控制两驱动轮电机实现机器人的运动控制。实验表明,该方法实现了机器人的自主导航,能够适应绝大部分光照强度的环境,并具有较好的实时性和可靠性。     

融合粒子滤波和环境标签矫正的巡检机器人自主定位算法

随着巡检机器人的需求量增加,巡检机器人在复杂环境中的自主定位问题越来越重要。提出了融合粒子滤波和环境标签矫正的自主定位算法,充分利用巡检机器人的工作环境特性和蒙特卡罗定位算法的特性,提高机器人自主定位的效率和效果。基于ROS建立了机器人仿真环境,对定位算法的效果进行了测试。实验结果表明融合粒子滤波和环境标签矫正的自主定位算法的效率和准确性有所提高,能够很快实现定位恢复。     

Robotics‐based telepresence using multi‐modal interaction for individuals with visual impairments

Although many assistive devices have been developed and utilized to aid in daily living, the most general assistive means for individuals with visual impairments are the walking cane and guide dogs. These assistive means are effective in assisting the user in navigating within an environment; however, the navigation space is limited to the proximal environment of the user. Thus, in this paper, we discuss a method to increase the range of accessibility to a remote environment through robotic embodiment that enables teleoperation and teleperception through multi‐modal feedback. In order to transform remote spatial information into a non‐visual modality, we present a framework for utilizing an RGB‐D‐based depth camera, a mobile robot, and a haptic interface for 3D haptic rendering to accomplish the goal of haptic exploration of a remote environment. Experiments with three different control methods for robot interaction are designed for users with and without visual impairments. Several hypothesis are built to study the correlation between control/feedback modality and performance in telerobotic operations. Results show that users performed best when combining semi‐autonomous navigation with 3D haptic exploration and also rated their experience with our system as fairly good. Copyright © 2014 John Wiley & Sons, Ltd.     

CNN‐based architecture for real‐time object‐oriented video coding applications

This paper presents a new CNN‐based architecture for real‐time video coding applications. The proposed approach, by exploiting object‐oriented CNN algorithms and MPEG encoding capabilities, enables low bit‐rate encoder/decoder to be designed. Simulation results using Claire video sequence show the effectiveness of the proposed scheme. Copyright © 2005 John Wiley & Sons, Ltd.     

Autonomous mobile robot based on behavior decision skill and control skill of the operator

This paper introduces a human skill base control algorithm using artificial neural networks and fuzzy reasoning for an autonomous mobile robot. Neural networks are used to select a suitable motion control pattern in actual environments. The back propagation algorithm adjusts the weights of the neural networks so that the selected motion control pattern corresponds to the action, which is obtained by the operator's behavior decision skill. To realize the selected motion control pattern, the orientation angle and the speed of the mobile robot are determined by fuzzy reasoning in which fuzzy rules are also automatically tuned so as to simulate the operator's control skill. We have implemented and tested the proposed control algorithm on an autonomous mobile robot and some experimental results demonstrate the effectiveness of the proposed control algorithm for the autonomous mobile robot. © 2000 Scripta Technica, Electr Eng Jpn, 131(2): 30–39, 2000     

自主空中加油飞行对接演示平台设计与实现

空中加油技术可以成倍增加战机的航程、留空时间、活动空间和有效载量,极大提高了战机的生存能力,增强航空兵的远程作战、快速反应和持续作战能力,而实现自主空中加油将大幅提高空中加油的快速性和稳定性.利用无人机搭建自主空中加油演示验证平台,将为相关算法的研究提供极大便利.文中设计了一套基于视觉的四旋翼自主空中加油演示系统,旨在模拟空中加油的真实环境,以验证视觉导航自主空中加油的可行性;搭建了一套硬件平台,实现各模块之间的通信;软件部分利用视觉解算出导航信息,并由PID算法求取飞行控制数据.实验结果表明,本平台各模块能够满足设计需求,实现了空中加油的飞行对接演示.