基于视差平面分割的移动机器人障碍物地图构建方法

作为自主移动机器人地表障碍物探测（GPOD）技术的一部分,提出了一种利用双目摄像机的视差图像 获取信息来构建机器人前方障碍物栅格地图的方法. 该方法融合了3 维立体视觉技术以及2 维图像处理技术,前者 依据视差图的直方图信息对视差图像进行自适应平面分割,把每个平面看作是3 维场景中的实物切片进而提取障碍 物3 维信息,后者通过计算各平面上的障碍物信息曲线来提取障碍物信息,把立体视觉数据从视差图像空间变换到 2 维的障碍物地图空间. 给出了该方法构建障碍物地图的整体过程,试验结果证明了该算法的有效性和精确性.     

井下移动机器人智能视觉避障研究

针对现有井下移动机器人避障方法在面对井下复杂障碍物时不能准确检测障碍物位置信息,对井下非线性障碍物不能准确进行避障控制等问题,提出了一种基于模糊控制的井下移动机器人智能视觉避障方法。首先采用双目立体视觉模组作为障碍物检测传感器,感知井下环境信息,实时检测障碍物分布情况,并构建占据栅格地图。然后通过八叉树结构模型构建三维点云,使用树状结构对点云数据进行结构化描述,并将其映射到占据栅格地图中,得到障碍物的区域分布情况。最后采用模糊控制策略对实时检测到的障碍物在占据栅格地图中的分布情况进行处理,将当前时刻障碍物在占据栅格地图中的分布情况和移动机器人运行速度作为模糊控制器的输入变量,通过模糊控制算法计算下一时刻移动机器人的转向角度和加速度,从而实现井下移动机器人的智能避障控制。根据移动机器人实际占据空间,设计外接包围盒进一步稳定控制算法,结合避障策略进行智能避障,避免移动机器人与障碍物发生碰撞。实验结果表明,该方法能够准确对井下障碍物分布情况进行描述,使移动机器人能够根据所设计的模糊控制规则准确自主地进行避障操作,从而实现自适应运动。     

基于地面视差分布的栅格地图建立方法

针对使用立体视觉建立环境地图方法存在信息不完整的问题,提出一种基于地面视差分布的栅格地图建立方法。利用地面视差分布在视差图中进行障碍物和地面点的检测,通过统一但参数值不同的投影模型将障碍物像素和地面点像素投影到栅格地图中,同时考虑立体视觉的量化和匹配误差、地面视差和栅格占据概率的空间分布。通过在非结构化环境中的实验表明,该方法可以实时地建立信息完整且准确的栅格地图。     

基于改进RANSAC的消防机器人双目障碍检测

针对消防机器人自主作业的障碍物快速检测问题,给出了一种基于改进随机采样一致性估计的双目障碍物检测算法。该算法首先采集双目视觉左右视图,进行半全局立体匹配获取视差信息,然后采用随机采样一致性估计的平面拟合法提取地平面模型,并采用预检验法和内点阈值限定法同时对随机采样一致性估计进行改进,从而提高算法效率,实现障碍物快速检测。实验结果证明该方法能够准确、快速检测障碍物,满足消防机器人作业需求。     

一种新颖的基于立体视觉的障碍物检测

本文针对车载双目视觉中的路面模型估计的难题提出了一种新颖而实用的算法,并将其应用于车前障碍物检测。首先,这里选取半全局视差匹配算法(SGM)获得稠密准确的视差图,并且在传统的v-视差算法的基础上引入加权Hough变换检测v-d平面中路面侧向投影的线性关系。然后,结合时序上的局部相关性和在v-d平面提取的多条直线拟合路面的投影特征曲线。最后根据该拟合曲线和视差图对当前帧进行自由空间和障碍物的分割和检测。     

基于双目视觉的障碍物高度检测

针对变电站设备巡检机器人的应用需求,提出了一种基于双目视觉的障碍物高度检测方法.采用双目测距原理对障碍物的距离信息进行检测,然后在图像中选择样本点,根据这些点在视差图中的三维坐标,利用改进的RANSAC算法,求取当前帧的路面的平面方程,并利用Kalman滤波对此平面方程进行估计和预测.最后利用点到平面距离公式求取障碍物的高度,得到三维环境的高度图,利用高度信息检测障碍物.实际应用表明:提出的方法能有效地克服光照变化和阴影对障碍物检测的影响,所求得障碍物的高度信息精度较高,能够满足需求,对于环境变化的适应性较强.     

基于主动式全景视觉的移动机器人障碍物检测

针对现有的移动机器人视觉系统计算资源消耗大、实时性能欠佳、检测范围受限等问题,提出一种基于主动式全景视觉传感器(AODVS)的移动机器人障碍物检测方法。首先,将单视点的全方位视觉传感器(ODVS)和由配置在1个平面上的4个红色线激光组合而成的面激光发生器进行集成,通过主动全景视觉对移动机器人周边障碍物进行检测;其次,移动机器人中的全景智能感知模块根据面激光发生器投射到周边障碍物上的激光信息,通过视觉处理方法解析出移动机器人周边障碍物的距离和方位等信息;最后,基于上述信息采用一种全方位避障策略,实现移动机器人的快速避障。实验结果表明,基于AODVS的障碍物检测方法能在实现快速高效避障的同时,降低对移动机器人的计算资源的要求。     

基于双目立体视觉的障碍物检测方法

基于双目立体视觉的障碍物检测方法,是一种基于双目视觉的V视差图检测障碍物的算法。利用生成的视差图之后再生成V-视差图,进而提取V-视差图当中的直线的信息,利用这些提取的直线的信息,就可以大致确定障碍物存在的区域,以此进行障碍物的检测。这样是一种对于光照和阴影等的干扰不是十分敏感,可以检测具备面特征的障碍物,可以用于复杂的背景之下的障碍物的检测。     

基于视觉传感器的障碍物检测

针对移动机器人双目视觉障碍物检测的实时性和准确性两大难题,提出了一种适用于室内复杂背景的障碍物检测方法。通过Retinex图像增强操作消除环境光照不均匀的影响;运用扫描线种子填充算法分割图像中的路面、背景和障碍物;通过二值化处理、边缘检测提取障碍物的轮廓信息和位置信息。在AS-RE轮式机器人平台上进行实验,实验结果表明,机器人能够在室内环境中稳定地实现自主避障功能,验证了提出的双目视觉障碍物检测算法的可行性。     

结合图像分割和点云分割的障碍物检测算法

针对单目图像检测障碍物的低可靠性和当前双目视觉检测障碍物的局限性的问题,提出一种结合图像分割和点云分割技术的双目视觉障碍物检测方法。通过设定检测深度范围,分割障碍物点云与道路点云;采用将分割出的障碍物点云对应的视差图与图像分割得到的子图进行比较的策略,有效解决对不同深度、倾斜面和不规则障碍物检测效果差的问题。通过实验验证了在获得稀疏三维点云的情况下,该方法对障碍物的检测具有较好的鲁棒性。     

Motion planning for mobile robots using a laser range finder

We have designed a mobile robot with a distribution structure for intelligent life space. The mobile robot was constructed using an aluminum frame. The mobile robot has the shape of a cylinder, and its diameter, height, and weight are 40 cm, 80 cm, and 40 kg, respectively. There are six systems in the mobile robot, including structure, an obstacle avoidance and driving system, a software development system, a detection module system, a remote supervision system, and others. In the obstacle avoidance and driving system, we use an NI motion control card to drive two DC servomotors in the mobile robot, and detect obstacles using a laser range finder and a laser positioning system. Finally, we control the mobile robot using an NI motion control card and a MAXON driver according to the programmed trajectory. The mobile robot can avoid obstacles using the laser range finder, and follow the programmed trajectory. We developed the user interface with four functions for the mobile robot. In the security system, we designed module-based security devices to detect dangerous events and transmit the detection results to the mobile robot using a wireless RF interface. The mobile robot can move to the event position using the laser positioning system.     

双足机器人实时障碍检测视觉系统

提出一种双足步行机器人的实时障碍检测视觉系统．基于图像平面与机器人行走地面之间的映射变换矩阵的唯一性准则，判别图像中的像点是否位于地面上，高于或低于地面的点被认为是障碍点，为减少实际行走过程中系统外部和内部参数变化对映射变换矩阵的影响，系统加入了在线校正映射变换矩阵模块．在提取出障碍物体边缘后，通过对其三维信息的简单恢复，建立了机器人行走空间的障碍投影图．该系统计算量小，可靠性强，能基本满足双足步行机器人实时避障的要求。     

Integration of a stereo vision system and a laser range finder for 3-D construction

In this article, we investigate the problem of integrating a binocular stereo vision system and a laser range finder to construct a 3-D map of the environment. The proposed scheme is realized by using the alignment parameters obtained in the 2-D map construction of the laser range finder for the 3-D data generated by the stereo vision system. The 2-D map alignment task is formulated as an optimization problem of minimizing the alignment errors between local maps and selected parts of the developing global map. The problem is then solved using the Simplex method. To increase the robustness of the searching process, multiple initial guesses are provided in the Simplex method. The performance of the proposed architecture is verified by experimental results from a mobile vehicle for obstacle avoidance.     

An algorithm for safe navigation of mobile robots by a sensor network in dynamic cluttered industrial environments

Mobile robots have been widely implemented in industrial automation and smart factories. Different types of mobile robots work cooperatively in the workspace to complete some complicated tasks. Therefore, the main requirement for multi-robot systems is collision-free navigation in dynamic environments. In this paper, we propose a sensor network based navigation system for ground mobile robots in dynamic industrial cluttered environments. A range finder sensor network is deployed on factory floor to detect any obstacles in the field of view and perform a global navigation for any robots simultaneously travelling in the factory. The obstacle detection and robot navigation are integrated into the sensor network and the robot is only required for a low-level path tracker. The novelty of this paper is to propose a sensor network based navigation system with a novel artificial potential field (APF) based navigation algorithm. Computer simulations and experiments confirm the performance of the proposed method.     

Attention-driven monocular scene reconstruction for obstacle detection, robot navigation and map building

In this paper, we present a feature-based approach for monocular scene reconstruction based on Extended Kalman Filters (EKF). Our method processes a sequence of images taken by a single camera mounted frontally on a mobile robot. Using a combination of various techniques, we are able to produce a precise reconstruction that is free from outliers and can therefore be used for reliable obstacle detection and 3D map building. Furthermore, we present an attention-driven method that focuses the feature selection to image areas where the obstacle situation is unclear and where a more detailed scene reconstruction is necessary. In extensive real-world field tests we show that the presented approach is able to detect obstacles that are not seen by other sensors, such as laser range finders. Furthermore, we show that visual obstacle detection combined with a laser range finder can increase the detection rate of obstacles considerably, allowing the autonomous use of mobile robots in complex public and home environments.     

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.