Robust object tracking for underwater robots by integrating stereo vision, inertial and magnetic sensors
Robust object tracking for underwater robots by integrating stereo vision, inertial and magnetic sensors
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通过集成立体视觉、惯性和磁传感器，为水下机器人提供强大的目标跟踪
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Song K. Choi
中科院分区：
文献类型：
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作者：
N. Sakagami;Song K. Choi
如本文所述，我们提出了一个强大的跟踪系统，立体视觉，IMU，和磁传感器的水下机器人，以估计一个静止的物体的位置，即使当对象是一个摄像机的视场（FOV）或发生遮挡。在水下机器人的操纵过程中，它们会受到外部干扰。他们的摄像机总是在移动。因此，图像中的对象意外地移出相机的FOV。如本文所述，我们将IMU和磁传感器与立体视觉传感器集成在一起，以鲁棒地估计物体的位置。在估计过程中，卡尔曼滤波器被用来估计传感器系统的方位。首先，我们进行数值分析，以调查所提出的方法对传感器噪声的估计精度。然后，进行了初步的实验，以证明所提出的方法对遮挡和移出FOV的鲁棒性。作为第一步，我们研究的跟踪性能与旋转运动的传感器系统。
As described in this paper, we propose a robust tracking system with a stereo vision, IMU, and magnetic sensor for underwater robots to estimate the position of a stationary object even when the object is out of the field of view (FOV) of a camera or occlusion occurs. During maneuvering of underwater robots, they are subject to external disturbances. Their cameras are always moving. Therefore, objects in an image move out of the FOV of a camera unexpectedly. As described in this paper, we integrate an IMU and a magnetic sensor with a stereo vision sensor to estimate an object’s position robustly. In the process of the estimation, Kalman filters are used to estimate the sensor system orientation. First, we conduct numerical analyses to investigate the estimation accuracy of the proposed method against sensor noise. Then, a preliminary experiment is conducted to demonstrate the robustness of the proposed method against occlusion and moving out of the FOV. As a first step, we examine the tracking performance with regard to rotational motion of the sensor system.