Time-of-Flight (ToF) is much more than a sensor technology—it functions like an additional, precise pair of eyes in industrial manufacturing. But what exactly is behind it, what advantages does ToF offer, and how is the technology evolving?

Who doesn’t know this situation? After a big shopping trip or a vacation, you stand in front of the car and wonder: How do I get all this into the trunk? Suitcases, shopping bags, maybe even a stroller—it seems impossible to fit everything in. But with a bit of spatial thinking and clever stacking, everything suddenly fits.

This ability to optimally arrange objects in a limited space is crucial not only in everyday life but also in industry. In factory halls, machines must precisely recognize, grasp, and place materials—and do so as error-free as possible. While we can improve our spatial thinking through practice, machines are helped by Time-of-Flight (ToF) technology. It gives them exact depth perception, allowing them to capture their surroundings in three dimensions and make optimized decisions—a key factor for the automation of the future.
 

Spatial Thinking and the Time of Flight Method

The goal is clear: fully automated robots that quickly detect objects and work efficiently. With the ToF method, this is possible: it measures the distance between the sensor and the object, providing precise 3D images. Three components make this possible: a light source emits modulated infrared light pulses, an image sensor captures the reflected light, and a computing unit calculates the time difference between the emitted and returning light. The principle is similar to a bat’s sonar—only with light instead of sound. The camera emits a laser beam, which is reflected by an object. The sensor measures the time it takes for the light to travel to and from the object, determining the exact distance to the object. A depth value is calculated for each pixel, creating a detailed depth map or point cloud.

Especially in logistics, the combination of ToF and 3D cameras offers decisive advantages. Unlike conventional 2D cameras, they capture not only the structure of an object but also its volume, shape, distance, and position in space. A vivid example of this is pallet picking: ToF cameras recognize not only the number of packages but also their dimensions and volume, allowing the available space to be optimally utilized. They work reliably regardless of contrasts or specific markings and function even in difficult lighting conditions, such as poorly lit rooms. Even moving objects are captured without problems. Compared to other 3D cameras, ToF systems are more compact, cost-effective, and less complex, making installation and integration significantly easier.
 

For an Improved Warehouse Automation

Among the pioneering models are the ToF cameras from Delta Electronics: The latest generation includes the ToF smart camera DMV-T and the RGB-D ToF camera DMV-TM, which are particularly well-suited for various applications and enable precise positioning, identification, and measurement for improved warehouse automation.

The ToF smart camera of the DMV-T series uses depth recognition technology to enable three-dimensional coordination in a space. The camera performs distance measurements, shape recognition, and object positioning even in complex environments such as poor lighting or cluttered spaces. With a range of up to 6 meters, a field of view of 67 degrees by 51 degrees, and 60 frames per second, the DMV-T camera is the standard model from Delta Electronics. With an integrated dual-core CPU, the camera is ideal for time-critical tasks such as pallet recognition on automated forklifts and positioning of objects in AS/RS systems. It features high accuracy (less than 1% error probability), a detection time of under 80 ms, and robust protection class IP67. Seamless integration into existing systems is ensured by the Ethernet interface.
 

Small Dimensions in Automated Guided Vehicles

The DMV-TM camera is specifically designed for integration into AGVs (Automated Guided Vehicles) and stacker cranes. Its lightweight and adaptable design, combined with precise navigation functions, enables collision avoidance and optimized performance in dynamic warehouse environments. It is 10 centimeters long, 3.5 centimeters high, and has a significantly wider field of view (FOV) of 105 degrees by 78 degrees compared to the standard model. This feature is crucial—after all, AGVs should primarily recognize the path ahead but also need a broad view of their surroundings for efficient use. For a 360-degree view, multiple mini-cameras would need to be installed on the AGV. For comparison, the human field of view is around 180 degrees—depending on age and person. The DMV-MT camera has a frame rate of 30 frames per second and a range of up to 4 meters. A key difference from the standard model is that the DMV-MT camera does not have an integrated processor. The image processing and corresponding computing power are therefore installed in the AGV or at the respective location—a reason for the smaller dimensions.
 

Automotive Industry, Logistics, and Hospitals

Warehouse optimization, reduction of pick and place tasks, fewer downtimes, increased flexibility and efficiency: ToF cameras have their core application area in the logistics industry. The automated takeover of pallet picking, container filling, or other logistics tasks relieves specialists and provides room for more demanding work. This is possible because cobots or AMRs can work fully automatically with the use of ToF cameras and can also be programmed to meet safety standards. Both the DMV-T and the DMV-TM are suitable for a wide range of applications in the areas of food and beverage packaging, electronics, automated production, and robot vision, demonstrating their versatility in various industries.