基于EKF的全景视觉机器人SLAM算法

研究全景视觉机器人同时定位和地图创建（SLAM）问题。针对普通视觉视野狭窄, 对路标的连续跟踪和定位能力差的问题, 提出了一种基于改进的扩展卡尔曼滤波（EKF）算法的全景视觉机器人SLAM方法, 用全景视觉得到机器人周围的环境信息, 然后从这些信息中提取出环境特征, 定位出路标位置, 进而通过EKF算法同步更新机器人位姿和地图库。仿真实验和实体机器人实验结果验证了该算法的准确性和有效性, 且全景视觉比普通视觉定位精度更高。     

An active trinocular vision system of sensing indoor navigation environment for mobile robots

Intelligent autonomous mobile robots must be able to sense and recognize 3D indoor space where they live or work. However, robots are frequently situated in cluttered environments with various objects hard to be robustly perceived. Although the monocular and binocular vision sensors have been widely used for mobile robots, they suffer from image intensity variations, insufficient feature information and correspondence problems. In this paper, we propose a new 3D sensing system, in which the laser-structured-lighting method is basically utilized because of the robustness on the nature of the navigation environment and the easy extraction of feature information of interest. The proposed active trinocular vision system is composed of the flexible multi-stripe laser projector and two cameras arranged with a triangular shape. By modeling the laser projector as a virtual camera and using the trinocular epipolar constraints, the matching pairs of line features observed into two real camera images are established, and 3D information from one-shot image can be extracted on the patterned scene. For robust feature matching, here we propose a new correspondence matching technique based on line grouping and probabilistic voting. Finally, a series of experimental tests is performed to show the simplicity, efficiency, and accuracy of this proposed sensor system for 3D environment sensing and recognition.     

基于RGB-D信息的移动机器人SLAM和路径规划方法研究与实现

移动机器人在各种辅助任务中需具备自主定位、建图、路径规划与运动控制的能力。本文利用RGB-D信息和ORB-SLAM算法进行自主定位,结合点云数据和GMapping算法建立环境栅格地图,基于二次规划方法进行平滑可解析的路径规划,并设计非线性控制器,实现了由一个运动底盘、一个RGB-D传感器和一个运算平台组成的自主移动机器人系统。经实验验证,这一系统实现了复杂室内环境下的实时定位与建图、自主移动和障碍物规避。由此,为移动机器人的推广应用提供了一个硬件结构简单、性能良好、易扩展、经济性好、开发维护方便的解决方案。     

Dynamic omnidirectional vision for mobile robots

Mobile robotic devices hold great promise for a variety of applications in industry. A key step in the design of a mobile robot is to determine the navigation method for mobility control. The purpose of this paper is to describe a new algorithm for omnidirectional vision navigation. A prototype omnidirectional vision system and the implementation of the navigation techniques using this modern sensor and an advanced automatic image processor is described. The significance of this work is in the development of a new and novel approach—dynamic omnidirectional vision for mobile robots and autonomous guided vehicles.     

A new multisensor fusion SLAM approach for mobile robots

This paper presents a novel method, which enhances the use of external mechanisms by considering a multisensor system, composed of sonars and a CCD camera. Monocular vision provides redundant information about the location of the geometric entities detected by the sonar sensors. To reduce ambiguity significantly, an improved and more detailed sonar model is utilized. Moreover, Hough transform is used to extract features from raw sonar data and vision image. Information is fused at the level of features. This technique significantly improves the reliability and precision of the environment observations used for the simultaneous localization and map building problem for mobile robots. Experimental results validate the favorable performance of this approach.     

基于粒子群算法的单目移动机器人地图创建

提出了一种基于粒子群优化算法的移动机器人地图创建方法,该方法模型简单,算法复杂度低,收敛速度快.首先对实验环境进行了描述,通过建立模型推导出了路标的坐标公式,提出了问题的关键.详细介绍了粒子群优化的工作原理,论述了该算法在地图创建中的具体实现.通过与算术平均法实验结果比较,证实了该方法的有效性.     

基于视觉SLAM–伺服框架的移动机器人指令滤波反步控制

针对移动机器人位姿镇定问题, 本文提出基于视觉同时定位与建图(simultaneous localization and mapping, SLAM)–伺服框架的指令滤波反步控制策略. 具体而言, 通过加速度层控制器设计进而积分得到的光滑速度信号, 减小SLAM视觉模块的预测位姿误差; 继而应用指令滤波器简化控制器设计的复杂求导运算, 减轻计算负担; 此外, SLAM模块利用运动信息与视觉信息的融合解决未知尺度问题, 降低未知深度造成的控制器设计复杂度. 通过李雅普诺夫理论可以证明闭环系统的稳定性. 仿真和实验结果最终验证了本文算法的有效性.     

视觉传感系统的自主移动机器人路径规划方法

在未知环境下,机器人很难快速获取周边环境信息并建立实时环境地图,实现自主运行.为此提出基于视觉导航的方法,利用全景摄像机作为机器人的视觉传感器系统采集环境信息,将彩色地图进行HSI空间下模糊聚类图像分割,得到环境二值图像;将图像进行栅格化处理来构建环境地图,运用8方向连接的Dijkstra进行全局路径规划,计算出最优路径,从而实现移动机器人的快速、自主运动.经过仿真实验证明,该方法有效且可行.     

Maintaining a common co-ordinate system for a group of robots based on vision

This work presents a novel approach to the problem of establishing and maintaining a common co-ordinate system for a group of robots. A camera system mounted on top of a robot and vision algorithms are used to calculate the relative position of each surrounding robot. The watched movement of each robot is compared to the reported movement which is sent over some communication link. From this comparison a co-ordinate transformation is calculated. The algorithm was tested in simulation and is at the moment being implemented on a real robot system. Preliminary results of real world experiments are being presented.     

Development of a vision non-contact sensing system for telerobotic applications

The study presented here describes a novel vision-based motion detection system for telerobotic operations such as distant surgical procedures. The system uses a CCD camera and image processing to detect the motion of a master robot or operator. Colour tags are placed on the arm and head of a human operator to detect the up/down, right/left motion of the head as well as the right/left motion of the arm. The motion of the colour tags are used to actuate a slave robot or a remote system. The determination of the colour tags’ motion is achieved through image processing using eigenvectors and colour system morphology and the relative head, shoulder and wrist rotation angles through inverse dynamics and coordinate transformation. A program is used to transform this motion data into motor control commands and transmit them to a slave robot or remote system through wireless internet. The system performed well even in complex environments with errors that did not exceed 2?pixels with a response time of about 0.1?s. The results of the experiments are available at: http://www.youtube.com/watch?v=yFxLaVWE3f8 and http://www.youtube.com/watch?v=_nvRcOzlWHw     

基于人工路标和立体视觉的移动机器人自定位

针对室内移动机器人的自定位问题,提出一种基于人工路标和双目视觉的室内移动机器人自定位方法。首先设计了一种可扩展的彩色人工路标,并给出路标的编码方法;然后利用色彩空间变换,直线交比不变性以及自适应窗口实现路标检测与识别;最后在分析双目立体视觉模型的基础上建立起基于路标的双目立体视觉定位模型,实现移动机器人的准确定位。实验结果表明,路标对光照和视觉传感器的采集位置具有较强的鲁棒性,定位精度能够满足室内移动机器人的定位要求。     

VISYR: a simulation tool for mobile robots using vision sensors

With the advent of mobile robots and inboard vision sensors mounted directly on the robot's wrist, new kinds of problems lie in the image processing field as, for example, dynamic scene analysis or motion estimation. The lack of flexibility of real experiments led us to implement at IRISA a general simulation tool devoted to the study of robots using moving vision sensors. VISYR allows us to simulate the image perceived by a robot of its environment during its motion.The first part of the paper is devoted to the modelling of the 3D scene containing complex objects and to the design of a suitable robotics vision sensor. In the second part, a new algorithm of dynamic management of the local data basis perceived by the sensor is presented. The parameters of the vision sensors are highly adjustable and VISYR is conceived to allow the fast development of algorithms using dynamic vision data.     

Analog circuit for motion detection using a CCD camera based on a biological vision system and its application to mobile robots

We have proposed an analog motion detection circuit based on a biological vision system. A charge coupled device (CCD) camera was used as the input in order to obtain an input image. By using the CCD camera, it is possible to detect the movement of an object as a high-resolution image. Because the unit motion detection circuit is constructed with eight metal oxide semiconductor (MOS) transistors and one capacitor, the structure of the unit circuit is simple. The test circuit was constructed on a circuit board using discrete MOS transistors. The results from the test circuit showed that it can detect the direction of motion. The test circuit was connected to a microcomputer in a mobile robot. It was clear from the results that the motion detection circuit can control a mobile robot.     

Development of the residual power prediction system for mobile robots

The article presents a multiple residual power prediction system to be applied in mobile robots or automation fields. The system contains multiple power detection units to measure multiple online power values. Each power detection unit uses four current sensors to measure the current variety, and uses weighted average method and redundant management method to calculate the exact current value, and isolates faulty measurement values. We use the proposed algorithms to be applied in voltage detection of each power detection unit. Then we can calculate the real-time power values according to the current and voltage measurement values. The control core of the power detection unit is HOLTEK microchip, and communicates with the data integration unit via wire I2C interface. The power detection units transmit the measurement values of current and voltage to the controller of the system. The main controller of the power detection system is PC-based system, and communicates with the data integration unit via wire RS232 interface. The main controller of the system can controls each power output ratio of the power sources, and predicts the power loading and the residual power for each power detection unit using auto-regression algorithm, and computes the residual time of mobile robots to work in the free space, and arrange the residual power of the enough power source to the weakness power sources using sequential single-item auction algorithm. In experiment result, the residual power prediction system can adjusts the power sources to increase the working time.     

Real-time people tracking for mobile robots using thermal vision

This paper presents a vision-based approach for tracking people on a mobile robot using thermal images. The approach combines a particle filter with two alternative measurement models that are suitable for real-time tracking. With this approach a person can be detected independently from current light conditions and in situations where no skin colour is visible. In addition, the paper presents a comprehensive, quantitative evaluation of the different methods on a mobile robot in an office environment, for both single and multiple persons. The results show that the measurement model that was learned from local grey-scale features could improve on the performance of the elliptic contour model, and that both models could be combined to further improve performance with minimal extra computational cost.     

Robust outdoor stereo vision SLAM for heavy machine rotation sensing

The paper presents a robust outdoor stereo vision simultaneous localization and mapping (SLAM) algorithm. It estimates camera pose reliably in outdoor environments with directional sunlight illumination causing shadows and non-uniform scene lighting. The algorithm has been developed to measure a mining rope shovel’s rotation angle about its vertical axis (“swing” axis). A stereo camera is mounted externally to the shovel house (upper revolvable portion of the shovel), with a clear view of the shovel’s lower carbody. As the shovel house swings, the camera revolves with the shovel house in a planar circular orbit, seeing differing views of the carbody top. During the swing, the SLAM algorithm builds a map of observed 3D features on the carbody and simultaneously using these landmarks to estimate the camera position. This estimated camera position is then used to compute the shovel swing angle. Two novel techniques are employed to improve the SLAM algorithm’s robustness in outdoor environments. First, a “Locally Maximal” feature selection technique for Harris corners is used to select features more consistently in non-uniformly illuminated scenes. Another novel technique is the use of 3D “Feature Clusters” as SLAM landmarks rather than individual single features. The Feature Cluster landmarks improve the robustness of the landmark matching and allow significant reduction of the SLAM filter computational cost. This approach of estimating the shovel swing angle has a maximum error of ±1° upon SLAM map convergence. Results demonstrate the improvements of using the novel techniques compared to previous methods.     

Developing a vision-based auto-recharging system for mobile robots

This article describes a vision-based auto-recharging system that guides a mobile robot moving toward a docking station. The system contains a docking station and a mobile robot. The docking station contains a docking structure, a control device, a charger, a safety detection device, and a wireless RF interface. The mobile robot contains a power detection module (voltage and current), an auto-switch, a wireless RF interface, a controller, and a camera. The controller of the power detection module is a Holtek chip. The docking structure is designed with one active degree of freedom and two passive degrees of freedom. For image processing, the mobile robot uses a webcam to capture a real-time image. The image signal is transmitted to the controller of the mobile robot via a USB interface. We use an Otsu algorithm to calculate the distance and orientation of the docking station from the mobile robot. In the experiment, the proposed algorithm guided the mobile robot to the docking station.     

Development of membrane controllers for mobile robots

The main contribution of this paper is the introduction of the new concept of membrane controller based on the structure and functioning of a deterministic numerical P system. The procedure for developing a membrane controller and for using it to control a mobile robot is explained and several test cases are given in which membrane controllers are used to control both simulated and real mobile robots and to generate various desired behaviours (obstacle avoidance, wall following, and follow the leader). The experiments reported in this paper validate the concept and prove that the performance of a membrane controller is comparable to or better than that of other controllers (such as fuzzy logic controllers).     

Centralized sensing and control of multiple mobile robots

We discuss the development ideas and merits of a single centralized station to provide supervision, sensing, control, intelligence and perhaps power to a colony of robots, organized for the performance of specific tasks. The consequence of such an approach is that each robot can be much simpler, smaller and less expensive, since no on-board sensing, control and intelligence are required. The issues to be studied concern tradeoffs in control (bandwidth, accuracy, channel capacity); relations between numbers of controllable robots and task suitability and representation for control.     

Development of a remote fault diagnosis system applicable to autonomous mobile robots

In this paper, the novel idea of using an autonomous mobile robot as a virtual local network is proposed as a system for the remote diagnosis of faults of a mobile robot. There are two primary points in this research. First, an objective of the research is to achieve a system with good expandability, i.e. one in which the diagnosis can be achieved whether there are many or few mobile robots to be diagnosed. To accomplish this goal by simply changing some system settings, a simple network management protocol (SNMP) structure is utilized. Within the developed diagnosis system, a mobile robot is taken as one of the management objects of the network management system (NMS). The SNMP, which is widely used in the NMS, is applied and adapted to the developed system as the communication protocol for exchanging diagnosis information. Moreover, by taking advantage of the active moving and sensing ability of autonomous mobile robots, an effective method of fault inference called a 'run-test' is discussed. By using this method, the accuracy of the diagnoses is improved. In the best-case scenario, the certainty of an accurate diagnosis increased from 20% (without using the 'run-test') to 93%. On the other hand, in some cases, the accuracy of the diagnosis results barely improved. On average, among the cases discussed in this paper, the accuracy of the diagnosis results improved about 2.1 times by the proposed method.