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Autonomous humanoid robot navigation using augmented reality technique

机译:使用增强现实技术的自主人形机器人导航

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This work presents a novel vision-based navigation strategy for autonomous humanoid robots using augmented reality (AR). In the first stage, a platform is developed for indoor and outdoor human location positioning and navigation using mobile augmented reality. The image sequence would be obtained by a smart phone's camera and the location information will be provided to the user in the form of 3D graphics and audio effects containing location information. To recognize a location, an image database and location model is pre-constructed to relate the detected AR-marker's position to the map of environment. The AR-markers basically act as active landmarks placed in undiscovered environments, sending out location information once detected by a camera. The second stage implements the same algorithm on an autonomous humanoid robot to be used as its navigation module. This is achieved by coupling the robot odometry and inertial sensing with the visual marker detection module. Using this system, the robot employs its vision system to enhance its localization robustness and allow quick recovery in lost situations by detecting the active landmarks or the so called AR-markers. The problem of motion blur resulting from the 6-DOF motion of humanoid's camera is solved using an adaptive thresholding technique developed to increase the robustness of the augmented reality marker detection under different illumination conditions and camera movements. For our experiments, we used the humanoid robot NAO and verified the performance of this navigation methodology in real-world scenarios.
机译:这项工作提出了一种使用增强现实(AR)的自主人形机器人的基于新的视觉导航策略。在第一阶段,使用移动增强现实开发了一个平台,用于室内和室外人类位置定位和导航。图像序列将通过智能手机的相机获得,并且将以3D图形和包含位置信息的音频效果的形式提供给用户的位置信息。要识别位置,预先构造图像数据库和位置模型以将检测到的AR标记的位置与环境的地图相关联。 AR标记基本上充当了处于未被发现的环境中的有效地标,发送由相机检测到的位置信息。第二阶段在自主人形机器人上实现相同的算法,以用作其导航模块。这是通过将机器人内径和与视觉标记检测模块耦合的惯性感测来实现的。使用该系统,机器人采用其视觉系统来增强其本地化鲁棒性,并通过检测有效地标或所谓的AR标记来允许在丢失情况下快速恢复。利用开发的自适应阈值技术解决了由人形相机6-DOF运动产生的运动模糊的问题,以在不同的照明条件和相机运动下增加增强现实标记检测的鲁棒性。对于我们的实验,我们使用人形机器人NAO并验证了这种导航方法在现实世界场景中的表现。

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