Position and depth (PD) estimation is one of the key characteristics of autonomous robots. Robots are often challenged to visualize an alien environment remotely, alongside the control mechanism, and estimate the PD of objects. For the robot to reach out to an object, it needs to know the object’s position in a 3-D space. The design of the robot’s vision system is crucial. In this research work, we propose a human intervention-based hybrid approach for estimation of PD of an object. Human intervention in the form of a mouse click on the laser spot of the object image/in the video created by a camera-laser setup is used to estimate the PD of an object. An error correction model is developed and evaluated for better performance of the proposed method. A comparison of the proposed method with that of the image processing method revealed that a hybrid approach is almost 50% better in accuracy. The test results indicate that this method could be very helpful in finding the depth of the object with better accuracy in a teleoperated semiautonomous robot.

中文翻译：

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基于人工干预的位置和深度估计混合方法的评估与误差校正

位置和深度（PD）估计是自主机器人的关键特征之一。机器人经常面临挑战，在控制机制旁边远程可视化外星环境，并估计物体的 PD。为了让机器人接触到一个物体，它需要知道物体在 3-D 空间中的位置。机器人视觉系统的设计至关重要。在这项研究工作中，我们提出了一种基于人工干预的混合方法来估计对象的 PD。以鼠标点击物体图像的激光点/在由相机激光设置创建的视频中的形式的人工干预用于估计物体的 PD。开发并评估了一个纠错模型，以提高所提出方法的性能。将所提出的方法与图像处理方法的比较表明，混合方法的准确率提高了近 50%。测试结果表明，该方法有助于在遥控半自主机器人中更准确地找到物体的深度。