Typical Applications for Time-of-Flight Cameras in Robotics and Logistics

Compared with other 3D cameras, ToF cameras are less expensive, more compact and less complex. They can be used to separate and measure objects in a scene. A ToF camera needs no contrast, no corners and edges, and can capture objects while they are moving.

Time-of-flight cameras are suitable for applications that require a large working distance, high speed and low complexity. If these properties are required and a low budget is more important than accuracy down to the millimeter, the time-of-flight process is the right choice. Volume measurements in logistics, palletising and de-palletising tasks as well as the control of autonomously driving vehicles in a logistics environment are suitable for time-of-flight (ToF) cameras.

An overview of the main time-of-flight applications

Volume measurement of individual objects is a major task of logistics. Alongside palleting, it is one of the most important factors to determine freight or shipping costs. The volume of the packed unit is measured. The freight costs are then determined based on that data. Automation of this process can bring significant savings, as freight costs tend to be mere estimates and/or based on information from the sender, which can be imprecise. Other promising fields of application that could benefit from volume measurement and location detection based on 3D data include automated warehouse management and efficient filling of containers and airplanes.

Palleting and depalleting are among the most time-intensive of logistics tasks and can provide a major efficiency boost if automated to work without disrupting the flow of operations. While these tasks might not seem particularly complex at first glance, closer inspection reveals more challenges than might be expected. A palleting or depalleting task is not purely about loading or unloading cargo. A palleting robot needs to determine precisely where the objects to be picked up are located, how large they are and their positioning relative to one another, to allow for an optimal grip position and to best use the existing space.

3D solutions here must be able to ‘see’ in real time like a person, including the location, size and gripping position; minute-long pauses to determine which object should be moved next are disruptive. ToF cameras are perfect tools for this task; the cameras identify the situation at a glance and calculate the necessary position on the fly.

Automated Guided Vehicles (AGVs) can also benefit from the time-of-flight technique. One or more ToF cameras generate a real-time image of the surroundings, allowing the AGV to review its environment quickly for hazards, or to follow a person. A ToF camera can be used to stitch together multiple individual snapshots of the environment, after which the AGV can then navigate the space. This offers massive benefits in terms of automation of production and logistics: processes can be accelerated, which in turn increases efficiency.