Yes, industrial handling robots can capture images and depth information of objects. This is usually achieved by integrating multiple visual sensors and depth perception devices, such as RGB cameras, 3D cameras, structured light sensors, LiDAR, or stereo vision systems. These devices can help robots obtain two-dimensional image information of objects and depth data in three-dimensional space, thereby accurately identifying, locating, and tracking objects.
Image information is mainly obtained by RGB cameras, which can recognize the color, shape, texture, and edge features of objects for object recognition and classification. And depth information is used to determine the specific position, posture (angle and direction), and relative distance to the surrounding environment of an object in space, which is crucial for robots to perform precise grasping and obstacle avoidance operations. For example, by obtaining a depth map, robots can know the exact height of an object on the table, or select the topmost object from multiple overlapping objects for grasping.
By fusing image and depth data, robots can construct a complete 3D perception model, enabling them to better complete tasks in complex or dynamic industrial environments. When robots need to handle irregularly shaped, stacked, overlapping, or partially occluded objects, depth information can help them determine which objects can be safely grasped and which may cause collisions or interference. At the same time, robots can also use this information to dynamically optimize the grasping points, improving the success rate of grasping and the accuracy of handling.
These visual and depth systems are often combined with artificial intelligence algorithms to enable robots to have higher-level environmental understanding capabilities. For example, robots can determine the type of object through image recognition, calculate the optimal path and grasping angle based on depth information, and even predict object movement trends or automatically adapt to changes in the work environment.
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