Vision Based Target Tracking and Collision Avoidance for Mobile Robots

A real-time object tracking and collision avoidance method is presented for mobile robot navigation in indoors environments using stereo vision and a laser sensor. Stereo vision is used to identify the target and to calculate its relative distance from the mobile robot while laser based range measurements are utilized to avoid collision with surrounding objects. The target is tracked by its predetermined or dynamically defined color. The mobile robot’s velocity is dynamically adjusted according to its distance from the target. Experimental results in indoor environments demonstrate the effectiveness of the method.     

3-D Tag-Based RFID System for Recognition of Object

Generally, object recognition in robotics has used vision, sonar, laser range sensors, etc. In this paper, the authors propose a new sensing technology based on radio frequency identification (RFID) to facilitate the autonomous recognition of objects. This technology uses a novel tag, named the 3-D tag, with which an object can be identified and its orientation together with location can be estimated. This paper presents the method for object recognition by analyzing the characteristics of the 3-D tag, and then validates the 3-D tag through several demonstrations showing its usefulness as an independent sensor for recognizing objects.     

悬臂掘进机自动导向和定位技术探索

介绍了掘进机自动导向和定位技术,分析和比较了基于全站仪、陀螺仪、电子罗盘、激光导向仪和视觉检测等的掘进机自动导向和定位技术的原理和特点,得出了如下结论:(1)基于陀螺仪和电子罗盘的自动导向和定位技术可实现自主导航,其它方法则需要给定参考坐标系;(2)以倾角仪作为俯仰角和横滚角检测传感器的装备技术更适合于水平巷道导向;(3)以巷道指向激光为参照系的方法更易于同煤矿现有自动导向和定位方式相结合。     

Design and research of automobile anti-collision warning system based on monocular vision sensor with license plate cooperative target

At present, detection method for the target vehicle based on monocular vision sensor uses the whole vehicle as targets. The automobile anti-collision technology proposed in this paper adopts monocular vision sensor for automobile measurement based on vehicle license plate cooperative target. Monocular vision sensor has advantages of good real-time performance and low cost. The technique can improve the detection capability of vehicle collision avoidance warning systems. In addition to the target vehicle positioning, it can also realize attitude determination. This technology eliminates the limits of road surface roughness and fluctuation. This paper designs the realization scheme of collision warning system based on monocular vision sensor from the automobile license plate cooperative target. Technology roadmap of automobile collision warning system is given. In this paper, license plate frame location is as the research background. The paper presents an analytic solution of positioning method for the license plate frame image. The method uses four vertex characteristics of license plate frame image to locate. Positioning speed of the method is fast. And it has a unique solution. This method can be used to positioning for the license plate frame. Simulation experiment is done for the collision warning location. The simulation results show that this method can locate the position for license plate frame image. License plate is regular shape, uniform, with identity recognition function markers on the automobile body. In the previous research on automotive collision warning and intelligent vehicle, we have not seen the research methods similar to the method introduced in this paper. The research enriches automobile anti-collision technology and theory of intelligent vehicle technology. It can also provide an auxiliary method for navigation and obstacle avoidance research for unmanned vehicle. It has certain scientific significance. Vehicle collision warning system can help the driver judgment, prompting warning, improving driving safety, and has broad application prospects.     

Spearmints: hardware support for performance measurements indistributed systems

Spearmints, a system of hardware components that can be easily interfaced to the nodes of an instrumented distributed system for monitoring or evaluation using event-triggered measurements, is described. Each machine of the target system must have one sensor that collects relevant events and marks them with global time stamps. The sensors can be attached to a common measurement system that samples the marked events on- or offline, orders them chronologically, and analyzes the resulting sequence. The design of Spearmints is based on providing a simple and universal tool that causes little interference and furnishes highly accurate measurements in distributed systems. As Spearmints only requires standard interfaces with its integration into an object system and its connection to a measurement system, it permits the use of a wide range of measurement systems for the evaluation of a variety of distributed systems     

Autonomous collision detection and avoidance for ARAGON USV: Development and field tests

This study addresses the development of algorithms for multiple target detection and tracking in the framework of sensor fusion and its application to autonomous navigation and collision avoidance systems for the unmanned surface vehicle (USV) Aragon. To provide autonomous navigation capabilities, various perception sensors such as radar, lidar, and cameras have been mounted on the USV platform and automatic ship detection algorithms are applied to the sensor measurements. The relative position information between the USV and nearby objects is obtained to estimate the motion of the target objects in a sensor‐level tracking filter. The estimated motion information from the individual tracking filters is then combined in a central‐level fusion tracker to achieve persistent and reliable target tracking performance. For automatic ship collision avoidance, the combined track data are used as obstacle information, and appropriate collision avoidance maneuvers are designed and executed in accordance with the international regulations for preventing collisions at sea (COLREGs). In this paper, the development processes of the vehicle platform and the autonomous navigation algorithms are described, and the results of field experiments are presented and discussed.     

激光飞秒手势识别算法建模及其简易导航微系统实现

为了解决演示场合展示办公应用的高性价比手势导航产品系统的需求，提出并阐述了基于高性能的激光飞秒测距传感和人工智能深度学习自适应进行手势识别的算法模型，做到了准确可靠、工效卓著和低成本，有力的突破了现有传统手势识别的局限。以此激光飞秒手势识别为核心，结合Lora短距离无线传输、WinUSB便捷接口和视窗控制软件处理的组合优势，独辟蹊径，实现了高性价比的简易导航微产品系统，使手势识别走向大众化常规应用，达到了教学、论坛、会展、会议等演示办公廉价便捷运用的期求。     

激光—相机系统语义栅格建图和路径规划

目的 SLAM（simultaneous localization and mapping）是移动机器人在未知环境进行探索、感知和导航的关键技术。激光SLAM测量精确，便于机器人导航和路径规划，但缺乏语义信息。而视觉SLAM的图像能提供丰富的语义信息，特征区分度更高，但其构建的地图不能直接用于路径规划和导航。为了实现移动机器人构建语义地图并在地图上进行路径规划，本文提出一种语义栅格建图方法。方法 建立可同步获取激光和语义数据的激光-相机系统，将采集的激光分割数据与目标检测算法获得的物体包围盒进行匹配，得到各物体对应的语义激光分割数据。将连续多帧语义激光分割数据同步融入占据栅格地图。对具有不同语义类别的栅格进行聚类，得到标注物体类别和轮廓的语义栅格地图。此外，针对语义栅格地图发布导航任务，利用路径搜索算法进行路径规划，并对其进行改进。结果 在实验室走廊和办公室分别进行了语义栅格建图的实验，并与原始栅格地图进行了比较。在语义栅格地图的基础上进行了路径规划，并采用了语义赋权算法对易移动物体的路径进行对比。结论 多种环境下的实验表明本文方法能获得与真实环境一致性较高、标注环境中物体类别和轮廓的语义栅格地图，且实验硬件结构简单、成本低、性能良好，适用于智能化机器人的导航和路径规划。     

基于极线约束的图像目标识别可信度评价方法

在图像辅助的惯性末制导系统中,提出了一种基于极线约束的图像目标识别可信度评价方法.当惯导系统给出的摄像机姿态或图像中目标的像素点位置存在误差时,为了平衡极线约束方程需要引入一个冗余量(residual),该冗余量可由惯导系统给出的摄像机两位置的相对运动及相应图像中目标点的像素位置计算得到.当惯导系统的姿态误差小于0.3°时,冗余量可以用来评价图像目标识别的可信度.理论推导及仿真实验证明,冗余量作为图像目标识别可信度的评价指标,具有良好的特性.     

激光异物清除器装置研究

目前清除架空输电线路上异物的方法主要是依靠人工方式或者借助无人机等遥控操作装置,这些操作耗时耗力且带电作业有一定的危险性,不能适应复杂的输电线路环境。随着激光技术的应用越来越广泛,利用激光清除电线异物已经成为现实。为了更好地实现切割效果,提高切割效率,文章结合数字图像处理技术,提出了一种基于转台伺服控制的激光除异物系统。通过架设在双自由度转台上相对固定的摄像头和激光发射装置达到识别跟踪并切除异物的效果,以图像解析结果为反馈,控制转台的转动方向和角度,从而确定激光发射的位置。为了有效确定切割目标,利用图像处理技术中的特征识别法进行异物识别与跟踪,并通过Hough直线检测识别出线缆,确定切割方向。实验表明,在转台满足精度指标的情况下可以有效清除规定范围内的目标异物,切割速度较快,适用范围较广。     

Automated barcode recognition for smart identification and inspection automation

Barcodes have been widely used in many industrial products for automatic identification in data collection and inventory control purposes. It is well known that in many stores laser bar-code readers are used at check-out counters. However, there is a major constraint when this tool is used. That is, unlike traditional camera-based picturing, the distance between the laser reader (sensor) and the target object is close to zero when the reader is applied. This may result in inconvenience in inspection automation because the human operator has to manipulate either the sensor or the objects. For the purpose of in-store or inspection automation, the human operator needs to be removed from the process, i.e. a robot with visual capability is required to play an important role in such a system. Moreover, an automated system is required to find, locate and decode barcodes on various document images even with low resolution compared with laser barcode readers (about 15,000 dots per inch) and can handle damaged bar codes. This paper proposes a smart barcode detection and recognition system (SBDR) based on fast hierarchical Hough transform (HHT). The back-propagation neural network (BPNN) is selected as a powerful tool to perform the recognition process. The paper presents an effective method to utilize the specific graphic features of barcodes for positioning and recognition purposes even in case of distorted barcodes. The first step the system has to perform is to locate the position and orientation of the barcode in the required material document image. Secondly, the proposed system has to segment the barcode. Finally, a trained back-propagation neural network is used to perform the barcode recognition task. Experiments have been conducted to corroborate the efficiency of the proposed method.     

Household robots look and learn: environment modeling and localization from an omnidirectional vision system

The work illustrates that a catadioptric omnidirectional vision system can be successfully applied for basic mobile robot navigation tasks, such as localization and environment learning. In combination with other capabilities of such a sensor, such as the recognition and tracking of humans, and because the price of such systems can be made low, this system is particularly suited for systems that are expected to operate in offices and homes in the near future, such as robotic servant systems, entertainment robots, and help for the elderly and disabled.     

A fuzzy-Bayesian approach to target recognition based on multisensor fusion

The Bayesian approach is widely used in automatic target recognition (ATR) systems based on multisensor fusion technology. Problems in data fusion systems are complex by nature and can often be characterized by not only randomness but also fuzziness. However, in general, current Bayesian methods can only account for randomness. To accommodate complex natural problems with both types of uncertainties, it is profitable to improve the existing approach by incorporating fuzzy theory into classical techniques. In this paper, after representing both the individual attribute of the target in the model database and the sensor observation or report as the fuzzy membership function, a likelihood function is constructed to deal with fuzzy data collected by each sensor. A similarity measure is introduced to determine the agreement degree of each sensor. Based on the similarity measure, a consensus fusion approach (CFA) is developed to generate a global likelihood from the individual attribute likelihood for the whole sensor reports. A numerical example is illustrated to show the target recognition application of the fuzzy-Bayesian approach. The text was submitted by the authors in English.     

Vision-based control of an autonomous disassembly station

In the EU about 10 millions of used cars have to be wrecked per year. So the disposal of these cars is of increasing importance in the next years. In a disassembly process for used cars one has to cope with the objects in an undefined state in contrast to the car production. For this purpose the use of vision-based control is motivated and a vision guided robotic system for an autonomous disassembly process is presented in this paper. An active stereo camera system is used as vision sensor. A combination of gray value and contour-based object recognition and a position measurement approach with implicit detection of occlusions is described. A system for the autonomous disassembly of wheels was successfully tested and shown in a final presentation. In this demonstrator a stereo vision system, a force–torque sensor, a task planning module, and a special unscrewing tool were integrated.     

计算机视觉中传感器规划综述

在摄影测量和目标识别计算机视觉的应用中,为了提高三维定位精度,有必要采用传感器规划策略,即预先在摄像机和照明参数进行规划,因为这样可以更有效地完成视觉任务,为了使人们对计算机视觉中传感器规划有一概略了解,首先分析了传感器和照明参数、特征检测约束、传感器和目标模型等影响传感器规划的各种因素;然后在总结传感器规划最近研究进展的基础上,根据传感器规划所使用方法等的不同,对传感器规划问题进行了分类,并将传感器规划问题归纳为组合优化的过程;最后指出传感器规划今后几个可能的研究方向。     

Building an environment model using depth information

The environment model's volumetric level, where information about free and occupied space is represented explicitly, is considered. At this model level, updating operations use raw sensory data from range sensors or processed data from any stereo or other depth recovery technique. In addition, this type of model can be used directly by path planning and navigation modules as well as for object recognition and manipulation modules. A system that uses the sensor-built model mode, in which there is initially little or no knowledge available about the domain and a model is incrementally constructed using the information provided by a sensor, is demonstrated. This mode of operation makes it possible to deal with unknown or dynamic environments     

Camera Recognition and Laser Detection based on EKF-SLAM in the Autonomous Navigation of Humanoid Robot

The ability of autonomous navigation of the humanoid robot under unknown environment is very important to real-life applications. EKF-SLAM based on the camera recognition and laser detection for humanoid robot NAO is presented in this paper. Camera recognition is used to recognize if the object is a landmark. Because the computational resources needed for the feature-based position estimation are quite expensive, the laser instead of the camera provides the position of the landmark. A fractional order proportional-integral (PI) controller is designed to reduce the derivation of the NAO robot from the desired path during autonomous navigation. Experiments show that the proposed method is valid and reliable for autonomous navigation of the NAO robot under unknown environment.