6-DOF Pose Estimation of a Robotic Navigation Aid by Tracking Visual and Geometric Features.
6-DOF Pose Estimation of a Robotic Navigation Aid by Tracking Visual and Geometric Features.
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DOI：
10.1109/tase.2015.2469726
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发表时间：
2015-10
期刊：
影响因子：
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通讯作者：
Tamjidi A
中科院分区：
文献类型：
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作者：
Ye C;Hong S;Tamjidi A
提出了一种用于视障者导航机器人的6自由度位姿估计方法。RNA使用单个3D相机进行PE和物体检测。所提出的方法处理相机的强度和范围的数据来估计相机的egomotion，然后使用扩展卡尔曼滤波器（EKF）作为运动模型来跟踪一组视觉特征的PE。在EKF中采用RANSAC过程来从两个图像帧之间的视觉特征对应性识别内点。仅使用内点来更新EKF的状态。EKF将自运动集成到世界坐标系中的相机姿态中。为了保持EKF的一致性，EKF使用摄像机和地板平面之间的距离（从范围数据中提取）作为摄像机z坐标的观测值。实验结果表明，所提出的方法的结果在室内环境中定位的RNA准确的姿态估计。基于PE方法，开发了一个用于在家庭环境中定位RNA的寻路系统。该系统使用估计的姿态和平面布置图来定位家庭环境中的RNA用户，并通过语音接口向用户通告兴趣点和导航命令。这项工作的动机是现有的视觉障碍导航技术的局限性。大多数现有的方法使用点/线测量传感器用于室内物体检测。因此，它们缺乏检测3D物体和定位盲人旅行者的能力。立体视觉已被用于最近的研究。然而，它不能为对象检测提供可靠的深度数据。此外，它往往会产生较低的定位精度，因为它的深度测量误差与真实距离成二次方增加。本文提出了一种新的方法，为盲人旅行者导航。该方法使用单个3D飞行时间相机进行6-DOF PE和3D物体检测，从而产生小尺寸但功能强大的RNA。由于相机的恒定深度精度，所提出的自运动估计方法的结果比现有的方法在一个较小的误差。提出了一种新的EKF方法，通过跟踪操作环境的视觉和几何特征，将自运动集成到RNA在世界坐标系中的6-DOF位姿中。所提出的方法大大减少了一个标准的EKF方法的姿态误差，从而支持更长的范围内的导航任务。该方法的一个局限性是它需要功能丰富的环境才能正常工作。
This paper presents a 6-DOF Pose Estimation (PE) method for a Robotic Navigation Aid (RNA) for the visually impaired. The RNA uses a single 3D camera for PE and object detection. The proposed method processes the camera’s intensity and range data to estimates the camera’s egomotion that is then used by an Extended Kalman Filter (EKF) as the motion model to track a set of visual features for PE. A RANSAC process is employed in the EKF to identify inliers from the visual feature correspondences between two image frames. Only the inliers are used to update the EKF’s state. The EKF integrates the egomotion into the camera’s pose in the world coordinate system. To retain the EKF’s consistency, the distance between the camera and the floor plane (extracted from the range data) is used by the EKF as the observation of the camera’s z coordinate. Experimental results demonstrate that the proposed method results in accurate pose estimates for positioning the RNA in indoor environments. Based on the PE method, a wayfinding system is developed for localization of the RNA in a home environment. The system uses the estimated pose and the floorplan to locate the RNA user in the home environment and announces the points of interest and navigational commands to the user through a speech interface. This work was motivated by the limitations of the existing navigation technology for the visually impaired. Most of the existing methods use a point/line measurement sensor for indoor object detection. Therefore, they lack capability in detecting 3D objects and positioning a blind traveler. Stereovision has been used in recent research. However, it cannot provide reliable depth data for object detection. Also, it tends to produce a lower localization accuracy because its depth measurement error quadratically increases with the true distance. This paper suggests a new approach for navigating a blind traveler. The method uses a single 3D time-of-flight camera for both 6-DOF PE and 3D object detection and thus results in a small-sized but powerful RNA. Due to the camera’s constant depth accuracy, the proposed egomotion estimation method results in a smaller error than that of existing methods. A new EKF method is proposed to integrate the egomotion into the RNA’s 6-DOF pose in the world coordinate system by tracking both visual and geometric features of the operating environment. The proposed method substantially reduces the pose error of a standard EKF method and thus supports a longer range navigation task. One limitation of the method is that it requires a feature-rich environment to work well.