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People Detection and Localization in Real Time during Navigation of Autonomous Robots

机译:自主机器人导航中的人员实时检测与定位

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Currently the navigation involves the interaction of the robot with its environment, this means that the robot has to find the position of obstacles (natural brands and artificial) with respect to its plane. Its environment is time-variant and computer vision can help it to localization and people detection in real time. This article focuses on the detection and localization of people with respect to plane of the robot during the navigation of autonomous robot, for people detection is used Morphological HOG Face Detection algorithm in real-time, where our goal is to localization people in the plane of the robot, obtaining position information relative to the X-Axis (left, right, obstacle) and with the Y-Axis (near, medium, far) with respect robot, to identify the environment in that it's located in the robot is applied the vanishing point detection. Experiments show that people detection and localization is better in the medium region (201 to 600 cm) obtaining 93.13% of accuracy, this allows the robot has enough time to evade the obstacle during navigation, the navigation getting 97.03% of accuracy for the vanishing point detection.
机译:目前,导航涉及机器人与其环境的相互作用,这意味着机器人必须在其平面上找到障碍物(自然品牌和人为)的位置。它的环境是时变,计算机愿景可以帮助它到本地化和人们实时检测。本文重点介绍了在自治机器人航行期间对机器人平面的人们的检测和本地化,对于人们的检测是实时使用形态的猪面部检测算法,我们的目标是将人们在飞机上定位机器人,获得相对于X轴(左,右,障碍物)和与adiach机器人的y轴(近的介质)的位置信息,以识别其位于机器人中的环境消失点检测。实验表明,人们检测和定位在中等区域(201至600厘米)更好地获得93.13%的精度,这使得机器人有足够的时间在导航期间逃避障碍,导航获得97.03%的消失点精度的97.03%检测。

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