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Tracking and intercepting pedestrians: a robotic approach to surveillance of critical infrastructures

机译:跟踪和拦截行人:机器人对关键基础设施的监控

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摘要

This dissertation presents an approach for the inclusion of technologies from the field of robotics into security and surveillance of outdoor critical infrastructures.ududNowadays, the systems used for these tasks are mainly reactive, meaning that they rely on alarms based on static sensors that require constant monitoring and a response from human operators. Therefore, the use of robotic systems can improve the capabilities of detecting and reacting to disruptions while reducing the risk for human operators.ududThe global objective of this work is to develop a system capable of performing a high level task in the context of security systems: the detection, tracking and interception of an intruder moving around, in an outdoors critical infrastructure.ududMoreover, the work should be focused not only on developing algorithms and strategies but also on testing them with real robots in realistic scenarios.ududDuring the Thesis, a modular system has been developed to carry out the global mission, thus, the process has been divided into several modules, namely: pedestrian detection, tracking, trajectory prediction, planning for interception and autonomous navigation. This modular design allowed developing and testing the modules independently from each other. Moreover, it also allowed us to use them in combination with external algorithms or to apply them to different applications. Furthermore, in order to facilitate the integration of the modules and real experimentation, software and communications architectures have been developed.ududThe pedestrians detection module is based on the fusion of information from two different sources: a 2D laser scanner and a camera. This module introduces two main novelties: the first one is the inclusion of an adaptive technique for projection of the region-of-interest, which addresses the problem of vertically localizing a projection from the laser into an image plane. The second one consists onudintroducing of a probability calibration step, applied before performing the fusion of information provided by both sensors, this allows reducing redundancy and correlation between two information sources.ududThe next module included in this work is the pedestrian tracking. It keeps updated a list of detected pedestrians, including their position and velocities. In order to do that, the algorithm processes the observations and determines whether or not each observation corresponds to a previously detected pedestrian. The main novelty on this algorithm is the introduction of a discriminative tracking procedure, where the uncertainty of the detection is taken into account. This means that, highly certain detections are used to confirm the presence of a human in the scene, meanwhile uncertain ones are used to keep track of its position over large areas.ududThe trajectory prediction module uses a comparison of the observed trajectory against possible routes in combinationudwith a simple modelling of the movements, to obtain a long-term prediction of the future trajectory of the pedestrian. Its main contribution is that it does not require any previous observation of pedestrian trajectories to obtain the prediction. Moreover, it can be adapted to any scenario since it only requires a cost-map of the infrastructure environment. Also, the integration of a motion model allows estimating a long term time-stamped prediction, which is required by the interception task.ududThe path planning for interception module constructs a tree of possible trajectories and evaluates each one of them in terms of their probability of intercepting the intruder according to its predicted trajectory. Subsequently, it extracts a route that likely intercepts a pedestrian, while avoiding both static and dynamic obstacles. The contribution in this case consisted on the modification and adaptation for this task, of an algorithm previously used for navigation in dynamic environments under uncertainty.ududA very important characteristic of the proposed system is the feasibility of being continuously updated as it is being executed. This means that any change in the movements of the pedestrian will be processed on-line and therefore, they will result in a modification of the trajectory of the pursuer robot. This makes it possible to obtain a system capable of performing a high level task, such as tracking and intercepting an intruder. No previous references have been found in literature presenting a real system performing that tasks in outdoor environments.ududThe system has been intensively tested and characterized by using simulation scenarios, and it has also being tested on three real world scenarios, with different sizes and obstacle distributions. Thus allowing to demonstrate the correct integration of all sub-modules of the thesis, as well as the capabilities of the detection, tracking and interception system as a whole.
机译:本文为将机器人技术领域的技术纳入室外关键基础设施的安全和监视提供了一种方法。 ud ud如今,用于执行这些任务的系统主要是被动的,这意味着它们依赖基于静态传感器的警报,需要持续的监控和操作人员的响应。因此,使用机器人系统可以提高对中断的检测和响应能力,同时降低操作人员的风险。 ud ud这项工作的全球目标是开发一种能够在以下情况下执行高级任务的系统:安全系统:在室外关键基础设施中对入侵者的检测,跟踪和拦截。 ud ud此外,这项工作不仅应着重于开发算法和策略,还应着重于在实际场景中使用真实的机器人对其进行测试。在论文发表期间,已经开发了执行全球任务的模块化系统,因此,该过程已分为几个模块,即:行人检测,跟踪,轨迹预测,拦截计划和自主导航。这种模块化设计允许彼此独立地开发和测试模块。而且,它还允许我们将它们与外部算法结合使用或将其应用于不同的应用程序。此外,为了促进模块的集成和实际实验,已经开发了软件和通信体系结构。 ud ud行人检测模块基于来自两个不同来源的信息融合:一个2D激光扫描仪和一个摄像头。该模块介绍了两个主要的新颖性:第一个是包含对感兴趣区域进行投影的自适应技术,该技术解决了将投影从激光器垂直定位到像平面的问题。第二个步骤是在执行两个传感器提供的信息融合之前应用概率校准步骤,这可以减少两个信息源之间的冗余和相关性。本文中的下一个模块是行人跟踪。它会不断更新检测到的行人的列表,包括他们的位置和速度。为此,算法处理观测值并确定每个观测值是否对应于先前检测到的行人。该算法的主要新颖之处在于引入了判别式跟踪程序,其中考虑了检测的不确定性。这意味着,高度确定的检测可用于确认场景中是否存在人员,同时不确定的检测可用于在大面积上跟踪其位置。 ud ud轨迹预测模块将观察到的轨迹与结合简单的运动建模方法获得可能的路线,以获得对行人未来轨迹的长期预测。它的主要作用是不需要对行人轨迹进行任何先前的观察即可获得预测。此外,由于它只需要基础架构环境的成本图,因此它可以适应任何情况。此外,运动模型的集成允许估算拦截任务所需的长期时间戳预测。 ud ud拦截路径规划模块会构造一棵可能的轨迹树,并根据以下内容评估每个轨迹:他们根据入侵者的预测轨迹拦截入侵者的可能性。随后,它提取一条可能会拦截行人的路线,同时避开静态和动态障碍物。在这种情况下,所做的贡献在于对此任务的修改和适应,这是先前用于不确定性下在动态环境中导航的算法。被执行。这意味着行人运动的任何变化都将被在线处理,因此,它们将导致跟踪机器人的轨迹发生变化。这使得可以获得能够执行诸如跟踪和拦截入侵者之类的高级任务的系统。文献中没有找到介绍在室外环境中执行该任务的真实系统的文献。 ud ud该系统已通过使用模拟方案进行了严格的测试和表征,并且还已在三种不同大小的实际方案中进行了测试和障碍物分布。因此,可以证明本文所有子模块的正确集成,以及整个检测,跟踪和拦截系统的功能。

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