Fail-safe 3D radar sensors for highly productive AGVs
3D radar sensor for collision avoidance in any environment
With the OndoSense 3D radar sensor solution for reliable collision avoidance, AGVs can operate with maximum reliability even in demanding environments or outdoors. The 3D radar sensor also detects objects that protrude into the AGV's driveway from above or below and uses special radar algorithms to detect people in the safety area. The OndoSense 3D sensor technology records the AGV with high precision, which enables a flexible adjustment of the safety zone. This reduces the travel distance and increases productivity.
The challenge
Reliable, fail-safe sensor technology
As mobile robots, Automatic Guided Vehicles (AGV) make a major contribution to automation and increased efficiency - for example in warehousing and logistics, in production but also in the health sector. High-performance sensors are required that deliver reliable results at all times in complex and difficult conditions. Otherwise, there is a risk of collisions with objects and people leading to unplanned downtime with costs of over USD 350 per second. With classic sensor technologies, collision-free navigation is only possible to a limited extent: Laser scanners usually only capture the environment horizontally and thus do not recognize potential obstacles that are below or above the scan plane. Inclined positions of the AGV and bumps on the road also limit the performance of the LiDAR sensors and represent further accident risks. Most laser, vision and ultrasonic sensors also struggle in harsh environments with dust, dirt, fog, smoke, heavy rain, extreme temperatures, flashes of light or strong vibrations.
The solution
Reliable, robust 3D collision avoidance
With OndoSense 3D radar sensors, AGVs can detect objects with extreme reliability, even in the most demanding situations or outdoors. This even applies to environments with dirt, rain, fire, steam, very high or low temperatures, poor lighting conditions or strong vibrations. In addition, people can also be detected using special radar algorithms. Since the 3D radar sensors, unlike image processing sensors, do not recognize individual persons, there are no data protection risks. Thanks to the large vertical opening angle of 110 degrees (elevation), the radar sensor also prevents collisions with objects that protrude into the route from below or above. This means that the safety zone can be adjusted e. g. to the height of the AGV. The OndoSense AGV radar also records the speed of the mobile transport robot with high precision without additional sensors. The advantage: The safety zone can be adapted directly and continuously to the driving speed and the calculated braking distance. This reduces the travel distance and increases productivity. The OndoSense 3D radar sensor system also offers a high ease of maintenance: In contrast to LiDAR or vision sensors, there are no moving parts that are susceptible to repair or sensitive optics that need to be cleansed. The result: a long product service life and reliability.
Industry range
Production
AGVs for transport, assembly, raw material handling
Logistics
AGVs for warehousing, container terminals
Health sector
Robots/AGVs for delivery & transport
Hotel business
Robots/AGVs for delivery & room service
Key features – your benefits
Full 3D collision avoidance – detects very high and low objects in the safety area (110° elevation)
Reliable in adverse environments – also suitable for the most difficult conditions (outdoor, etc.)
Detection of human beings without recognizing individual persons: no data protection risks
Precise speed measurement – for an adaptive configuration of security zones
Your inquiry on our solution
Tell us about your application. Let us know how we may help you.
Are you interested in implementing our solution in your company? Do you have any questions about the application or our products? We will provide you with answers, advise you on the use of OndoSense radar sensors and work out a solution for your individual challenge together with you.
