Terabee's new TeraRanger Hub Evo provides 'lean sensing' for robotics



Terabee, which created the TeraRanger Time of Flight distance sensors, has announced the release of the ​TeraRanger Hub Evo, which the company describes as a new generation “plug and play solution for using multiple distance sensors.”

A “small, octagonal, PCB,” the TeraRanger Hub Evo allows users to connect up to eight ​TeraRanger Evo distance sensors and place them in whatever configuration they might need, so that they can monitor and gather data from just the areas and axes they need, and create custom point clouds, optimized to their application​.

The Hub offers a variety of capabilities, as it provides power to each sensor, prevents sensor crosstalk, synchronizes the data and outputs an array of calibrated distance values in millimeters. It also has a built-in IMU.

“We’ve been advocating the use of ‘​selective point clouds​’ for a while,” says Max Ruffo, CEO of Terabee.

“We understand that people often feel more secure by gathering millions of data points, but let’s not forget that every point gathered needs to be processed. This typically ​requires complex algorithms and lots of computing power​, relying heavily on machine learning and AI as the system grows in complexity. And as things become more complex, the computational demands of the system rise and ​the potential for hidden failure modes also increases​.”

Max goes on to explain that “taking the mechanical engineering approach - trying to solve the problem in the easiest way possible - ‘​lean-sensing​’ could well be ​a less complex, lower cost and more reliable solution in many applications.”

In this example, Terabee uses a large mobile robot used for wrapping pallets with thin film to showcase lean-sensing and selective point cloud creation. The company says that in the real-world of logistics, “pallets are often loaded with random shapes and sometimes these can be overhanging the edges of the pallet or the items they are loaded on top of.”

“Our customer needed a contactless method for their robot to rotate around a pallet of goods at high speed (up to 1.3 meters per second) to apply thin film pallet wrap,” Max explains. “As well as being fast, the system needed to be computationally lean (to ensure robustness) and also cost-effective.”

What Terabee created uses just 16 single-point distance sensors, operating as small arrays, to generate selective point clouds.

To maintain a safe and consistent distance to the pallet, three sensors look to the side. Five sensors look forward to provide collision avoidance and safety in the event that something or someone enter the path of the robot.

Terabee says that “another array, this time eight sensors, looks up into the area where pallet contents are,” and in real-time, this array builds a “lean point cloud of the pallet contents, including any irregularities such as overhangs.” This three-dimensional data is then fed to the control system so that the two-dimensional trajectory of the robot can be adapted to make sure the robot avoids any overhanging items, and optimizes its path for pallet wrapping.

Just 16 numbers—along with some minor data from wheel odometry and the IMU—are fed to the control system, which allows three-dimensional data points to change the two-dimensional trajectory of the robot, in real time and at high speed.

Max says that “the solution could probably run just as well with fewer sensors,” adding that the company is now testing “to see how few sensors can be used without compromising performance, reliability or safety.”

“We’ll continue to develop our Hub and multi-sensor concept, making it easy for people to use our sensors in configurations to meet their specific needs,” Max says. “It’s already proven to be a very popular way for people to prototype and use multiple sensors for drones, robotics, industrial applications and more recently some smart city use cases too.”