Development of an autonomous bridge deck inspection robotic system

The threat to safety of aging bridges has been recognized as a critical concern to the general public due to the poor condition of many bridges in the United States. Currently, the bridge inspection is conducted manually, and it is not efficient to identify bridge condition deterioration in order to facilitate implementation of appropriate maintenance or rehabilitation procedures. In this paper, we report a new development of the autonomous mobile robotic system for bridge deck inspection and evaluation. The robot is integrated with several nondestructive evaluation (NDE) sensors and a navigation control algorithm to allow it to accurately and autonomously maneuver on the bridge deck to collect visual images and conduct NDE measurements. The developed robotic system can reduce the cost and time of the bridge deck data collection and inspection. For efficient bridge deck monitoring, the crack detection algorithm to build the deck crack map is presented in detail. The impact‐echo (IE), ultrasonic surface waves (USW), and electrical resistivity (ER) data collected by the robot are analyzed to generate the delamination, concrete elastic modulus, corrosion maps of the bridge deck, respectively. The presented robotic system has been successfully deployed to inspect numerous bridges in more than ten different states in the United States.     

基于蛇形机器人桥梁缆索无损检测系统的研究

基于桥梁缆索无损检测的特殊性,且针对目前桥梁缆索检测智能化的需要,介绍了一种新型的检测系统,即基于桥梁缆索检测的蛇形机器人.此蛇形机器人具有较大的自由度,有非常好的环境适应能力.在分析蛇形机器人的本体结构特点和运动机理的基础上,并根据桥梁缆索的特性,研究了基于蛇形的器人桥梁缆索的无损检测系统.通过实验证明:此无损检测系...     

Autonomous Exploring System Based on Ultrasonic Sensory Information

An autonomous exploring system for a mobile robot is presented in this article. The system consists of an ultrasonic range sensor (URS) module and a novel method for building a map from exploration of an environment. Instead of random exploration, the proposed approach provides a systematic and efficient strategy to build the map by means of some preferential points. Taking a multitude of observations or measurements by sonar sensors, a mobile robot derives a virtual polygonal map from a set of regressed segments, partial prior known environmental information, and some inference rules for vertices. Additionally, the concept of safe zones is also introduced in the system to keep the mobile robot safe during exploration. Based on the identified virtual map, a searching method is used to select a next best observation to collect the most sufficient information. Several experiments are given to demonstrate the performance of this proposed approach.     

一种输电线路巡检机器人控制系统的设计与实现

介绍了一种超高压输电线路巡检机器人控制系统的设计与实现方法．根据巡检作业任务的要求，采用遥控与局部自主相结合的控制模式实现巡检机器人沿线行走及跨越障碍．设计了巡检机器人有限状态机模型，实现了机器人遥控与局部自主控制的有机结合．采用基于激光传感器定位的方法实现了巡检机器人的自主越障控制．实验结果表明，该机器人可实现沿线行走及自主跨越障碍，从而验证了控制系统设计的有效性与合理性．     

Development and field test of the articulated mobile robot T2 Snake-4 for plant disaster prevention

Abstract

In this work, we develop an articulated mobile robot that can move in narrow spaces, climb stairs, gather information, and operate valves for plant disaster prevention. The robot can adopt a tall position using a folding arm and gather information using sensors mounted on the arm. In addition, this paper presents a stair climbing method using a single backward wave. This method enables the robot to climb stairs that have a short tread. The developed robot system is tested in a field test at the World Robot Summit 2018, and the lessons learned in the field test are discussed.     

高压巡线机器人穿越耐张杆塔的控制算法

通过对高压输电线路中耐张杆塔的电磁场进行理论和试验分析,根据电磁场的分布规律对导航电磁传感器的布置进行试验研究,提出了采用传感器补偿算法的控制对策。试验表明:采用传感器补偿算法的控制对策,巡线机器人自主穿越耐张杆塔障碍是可行的。     

多传感器信息融合在移动机器人定位中的应用

机器人自定位是实现自主导航的关键问题之一。为了满足机器人在导航时精确定位的要求,提出一种基于多传感器信息融合的自定位算法。根据对机器人运动机构的分析和运动机构间的刚体约束,建立起机器人的运动学模型;由传感器的工作原理建立里程计和超声波传感器的观测模型;利用扩展卡尔曼滤波(EKF)算法将里程计和超声波传感器采集的数据进行融合;最后,由匹配的环境特征对机器人的位置进行修正,得到精确的位置估计。实验结果表明:该算法明显地消除了里程计的累计误差,有效地提高了定位精度。     

Echolocation — From range to outline segments

A ring of ultrasonic sensors mounted on a mobile robot is used to map a room. The sensors are modelled with an arc model: the object causing the reflection lies on an arc with radius equal to the range and arc angle equal to twice the beam angle. By fusing sensing with motion, a surface is displayed as a sequence of arcs. In this paper, the algorithm for obtaining outline segments from the arcs is presented.     

遥自主移动机器人系统设计及实现

为了解决移动机器人在特定环境下自主性不强的问题,构建了自主移动机器人的遥操作控制系统。通过无线网络传输的通信方式实现了经过透视解算展开后的全景图像的传输和基于USB操纵杆的多功能远程控制平台的开发。详细介绍了机器人利用超声波传感器进行自主模糊避障的算法,利用USB操纵杆对机器人遥操作的程序实现,以及全景摄像头透视解算和视频压缩的方法。实验结果表明,构建的遥操作控制系统可以实现良好的人机交互,使移动机器人的自主性更强,更加智能化。     

超高压输电线路巡检机器人越障控制问题的研究

给出了一种超高压输电线路巡检机器人控制系统的设计与实现方法．根据机器人的作业任务,提出了基于传感器信息、约束信息以及动作反馈信息作为输入,产生式系统作为动作输出的越障控制方式．仿真结果表明此方法对于机器人的越障过程是有效的．     

Concrete Defects Inspection and 3D Mapping Using CityFlyer Quadrotor Robot

The concrete aging problem has gained more attention in recent years as more bridges and tunnels in the United States lack proper maintenance. Though the Federal Highway Administration requires these public concrete structures to be inspected regularly, on-site manual inspection by human operators is time-consuming and labor-intensive. Conventional inspection approaches for concrete inspection, using RGB image-based thresholding methods, are not able to determine metric information as well as accurate location information for assessed defects for conditions. To address this challenge, we propose a deep neural network (DNN) based concrete inspection system using a quadrotor flying robot (referred to as CityFlyer) mounted with an RGB-D camera. The inspection system introduces several novel modules. Firstly, a visual-inertial fusion approach is introduced to perform camera and robot positioning and structure 3D metric reconstruction. The reconstructed map is used to retrieve the location and metric information of the defects. Secondly, we introduce a DNN model, namely AdaNet, to detect concrete spalling and cracking, with the capability of maintaining robustness under various distances between the camera and concrete surface. In order to train the model, we craft a new dataset, i.e., the concrete structure spalling and cracking (CSSC) dataset, which is released publicly to the research community. Finally, we introduce a 3D semantic mapping method using the annotated framework to reconstruct the concrete structure for visualization. We performed comparative studies and demonstrated that our AdaNet can achieve 8.41% higher detection accuracy than ResNets and VGGs. Moreover, we conducted five field tests, of which three are manual hand-held tests and two are drone-based field tests. These results indicate that our system is capable of performing metric field inspection, and can serve as an effective tool for civil engineers.      

基于ROS与Kinect的移动机器人同时定位与地图构建

同时定位与地图构建(SLAM)技术一直以来都是移动机器人实现自主导航和避障的核心问题,移动机器人需要借助传感器来探测周围的物体同时构建出相应区域的地图。由于传统的1D和2D传感器,如超声波传感器、声呐和激光测距仪等在建图过程中无法检测出Z轴(垂直方向)上的信息,易增加机器人发生碰撞的概率,同时影响建图结果的精确度。本文利用Kinect作为机器人SLAM的传感器,将其采集到的三维信息转化成二维的激光数据进行地图构建,同时借助机器人操作系统(robot operating system,ROS)进行仿真分析和实际测试。结果表明Kinect可以弥补1D和2D传感器采集信息的不足,同时能够较好的保持建图的完整性和可靠性,适用于室内的移动机器人SLAM实现。     

An accurate and robust visual-compass algorithm for robot-mounted omnidirectional cameras

Due to their wide field of view, omnidirectional cameras are becoming ubiquitous in many mobile robotic applications.  A challenging problem consists of using these sensors, mounted on mobile robotic platforms, as visual compasses (VCs) to provide an estimate of the rotational motion of the camera/robot from the omnidirectional video stream. Existing VC algorithms suffer from some practical limitations, since they require a precise knowledge either of the camera-calibration parameters, or the 3-D geometry of the observed scene. In this paper we present a novel multiple-view geometry constraint for paracatadioptric views of lines in 3-D, that we use to design a VC algorithm that does not require either the knowledge of the camera calibration parameters, or the 3-D scene geometry. In addition, our algorithm runs in real time since it relies on a closed-form estimate of the camera/robot rotation, and can address the image-feature correspondence problem. Extensive simulations and experiments with real robots have been performed to show the accuracy and robustness of the proposed method.     

多通道超声系统在管道内检测中的应用

多通道超声自动检测是管道腐蚀内检测的关键技术。根据管道内检测的要求,研制了具有20个探头的数字式多通道超声管道内检测系统。检测系统采用主从结构,检测板卡通过PCI总线与嵌入式计算机通信,并利用高速切换开关扩展通道数。超声回波信号处理采用Burg最大熵谱估计法,得到管道壁厚数据。经标准实验管段检测证明,检测系统能够检测管道内外腐蚀缺陷,数据采集、处理、存储及图像显示满足管道内检测要求,应用前景较好。     

Obstacle avoidance algorithm for visual navigation using ultrasonic sensors and a CCD camera

An obstacle-avoidance algorithm is presented for autonomous mobile robots equipped with a CCD camera and ultrasonic sensors. This approach uses segmentation techniques to segregate the floor from other fixtures, and measurement techniques to measure the distance between the mobile robot and any obstacles. It uses a simple computation for the selection of a threshold value. This approach also uses a cost function, which is combined with image information, distance information, and a weight factor, to find an obstacle-free path. This algorithm, which uses a CCD camera and ultrasonic sensors, can be used for cases including shadow regions, and obstacles in visual navigation and in various lighting conditions. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

自主移动机器人室内定位方法研究综述

自主移动机器人的室内定位作为机器人研究领域中最基本的问题已被广泛研究。根据定位技术和传感器的不同,将室内定位方法分为航迹推算定位、地图匹配定位和基于信标定位三类。详细介绍了超声波网络定位系统和基于无线射频识别（RFID）的定位方法。对几种基于概率的定位算法做了分析和对比,并对自主移动机器人室内定位方法的研究方向做了展望。     

基于虚拟传感器和脚本控制的移动机器人越障仿真

为了实现移动机器人越障运动过程的仿真，运用机械系统仿真软件ADAMS，构建虚拟传感器并编写脚本仿真程序。实例分析表明，基于脚该控制，可以完成复杂运动的仿真。通过三维动画既可以观察移动机器人越障运动过程，同时还可绘制仿真曲线，观察运动过程中可能出现的问题。     

Nondestructive evaluation sensor fusion with autonomous robotic system for civil infrastructure inspection

Civil infrastructure inspection is crucial to maintaining the quality of that infrastructure, which has a great impact on the economy. Performing this inspection is costly work that requires workers to be trained on how to use varying technologies, which can be error prone when performed manually and can result in damage to the infrastructure in some cases. For this reason, nondestructive evaluation (NDE) sensors are preferred for civil infrastructure inspection as they can perform the necessary inspection without damaging the infrastructure. In this paper, we develop a fully autonomous robotic system capable of real‐time data collection and quasi‐real‐time data processing. The robotic system is equipped with several NDE sensors that allow for a sensor fusion method to be developed that successfully minimizes inspection time while performing adequate inspection of areas that require more in‐depth data to be collected. A detailed discussion of the inspection framework developed for this robotic system, and the dual navigation modes for both indoor and outdoor autonomous navigation is presented. The developed robotic system is deployed to inspect several infrastructures (e.g., parking garages, bridges) at and near by the University of Nevada, Reno campus.     

Intelligent environment recognition and prediction for NDT inspection through autonomous climbing robot

This paper presents a novel approach to environment mapping prediction with focus on autonomous climbing robot to NDT (Non-Destructive Technique) inspection. In industrial installations, the inspection of non-planar surfaces requires that NDT probes passe on whole surface, while the autonomous robot navigates over an unknown environment based only on its perception abilities. However, the path planning of inspection is not a trivial task specially when there is no precise information about environment. In this work, a special kind of climbing robot is used to inspect large metallic surfaces such as spherical pressure vessels used to store Liquified Petroleum Gas (LPG). The robot has adherence skills that allow it to safely navigate through the internal and external surface of the vessel. As a result, robot mobility suffers from hard magnetic adhesion constraints. A new approach is proposed to environment detailed prediction, including specific characteristic (like weld beads and plates) of inspected surface. The goal is the automatic extraction of some environment characteristics to predict the storage tank dimensions and robot localization, based on a group of 3D perception sources (laser rangefinder, light detection and ranging and depth camera) mounted over a rolling platform to improve its reach. The environment prediction is carried out after the robot visually detects two or more weld beads corners. A multi-measuring environment is firstly build by Fuzzy data fusion of the different perception measurements allowing to estimate plates and weld beads based on design and safety standards. Virtual and real experiments are carried out to illustrate proposed method performance.