RGB D Sensor

RGB-D sensors, which capture both color and depth information, are increasingly used for 3D scene understanding and robotic applications. Current research focuses on improving accuracy and robustness in challenging environments, often employing techniques like Kalman filtering for viewpoint estimation and deep learning models (e.g., Temporal Convolutional Networks) for tasks such as hysteresis compensation in robotic manipulators and depth estimation from low-resolution sensors. These advancements enable applications ranging from people counting and indoor navigation assistance for the visually impaired to precise object manipulation and 3D reconstruction, improving the accuracy and efficiency of various systems.