Developments in AGVs and ARs are moving fast. Robots are increasingly driving (semi)autonomously through production environments or logistics centers, for example. The application of sensors to make all movements functional and safe are crucial in this process. One of the measurement principles widely used in autonomous vehicles is Lidar; a robust laser-based technique for measuring distances and speeds to prevent collisions. But Lidar can do more. This is evident, among other things, from the two novelties with which Vierpool recently supplemented its program: the LGS-A10 lidar scanner and the LGS-N25.
Lidar is the abbreviation for "light direction and ranging" and the name of a technique that allows non-contact measurement of relative distances. In this way, the technique can be used to prevent autonomous vehicles from colliding with other elements in the environment. In addition, the measurement technique can be used remotely to perform shape and size checks. For example, when palletizing boxes.
The operation of Lidar relies on emitting a laser beam and measuring the time it takes for the laser beam to return - after reflection. This is called the ToF principle; Time of Fligth. Because this process repeats itself at every 0.25° displacement up to 360° around, the operation is fairly similar to that of a radar system. One difference is the (much) higher accuracy because the wavelength of laser light is many times smaller than that of radar.
Marco de Jong is Sales & Account Manager at Vierpool and has extensive experience with Lidar products from the Datasensing representation. "The Lidar technique is now widely known and is also successfully used in many applications. Datasensing also has some lidar-based solutions in its program that differ from an average solution in important ways. The most important is the compact design and low build which makes the sensors suitable for integration into almost any application, including Automated Guided Vehicles (AGV), Automated Mobile Robots (AMR), Automated Guided Forklifts (AGF) and Automated manufacturing machines."
The two most recent additions are the LGS-A10 Lidar scanner and LGS-N25 Lidar. To start with the latter, the LGS-N25 Lidar was specifically developed for vehicle navigation and guidance, environmental mapping and object profiling in industrial applications. De Jong: "The small design makes the product particularly suitable for intralogistics, as just mentioned, but also for use in automated production or logistics plants for access monitoring and shape control."
Thereby, the functionality is broad with 360° measurement, highly accurate and reliable operation up to distances of 25 meters and up to 225,000 measurement points per second. Its compact nature is reflected in its dimensions of 65x65x70 mm. The high protection class of IP67 also makes this Lidar scanner suitable for outdoor applications. Think of automatic and autonomous lawnmowers or other applications in agri.
The LGS-A10 is similar in many ways to the LGS-A10 but is distinguished in part by the ability to set up to 16 zones. In addition, the user has the ability to choose from three simultaneous detection outputs, five detection options and 10 response times. "This allows the component to be fine-tuned to its specific task. The application range is also somewhat broader and extends to shape recognition. This means that the application recognizes whether, for example, a pallet of boxes is arriving that is allowed to continue in the palletizing line or whether a human being is coming to take a look that is not allowed to pass through for safety reasons."
De Jong concludes, "Of course, you can still mention a lot of technical details, but the most important thing is that Datasensing's Lidar components have a limited installation space, work with high accuracy within a relatively large area, and are also able to withstand a bump. An excellent basis for further improving the safety of autonomous vehicles and expanding their range of application, allowing the industry to work more efficiently, safely and ergonomically."
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