Skip to content
Home » Human-robot collaboration (cobots)

Human-robot collaboration (cobots)

50% more productivity for cobots – with smart motion sensors

Reliable pre-collision radar sensors for human-robot collaboration

 

Radar sensors offer a reliable and highly precise solution for collision avoidance in human-robot collaboration. Smart motion sensors capture human movements in production environments with cobots using algorithms for artificial intelligence. Static protection zones can be avoided or limited with real-time situation analysis. This reduces expensive downtime and increases the productivity of the cobots by up to 50 percent.

Robot welding. ©ipopba - Adobe Stock

The challenge

Billion-dollar damage from lost production

More and more robots are used in industrial production for jobs that are too dangerous for humans or that robots can perform more efficiently. The working areas of man and machine are increasingly not separated from each other. The main reason for this development is that there is a high productivity potential in collaboration. However, collisions between machines and workers keep on happening consistently. This not only causes injuries, but also production losses with billions in damage. More than 80% of all manufacturing companies are faced with unplanned downtimes. On average, production plants are idle 800 hours a year. This downtime costs up to EUR 20,000 per minute. The solution are so-called "pre collision" sensors: These identify people who are approaching the robot and stop or restrict the machine movements. Yet the sensors currently available are only partially reliable: Print mats are used to locate people, but only provide rough, two-dimensional information about the current position. A collision with a robot arm cannot be ruled out, since the head or arms are not always exactly above the pressure point of the feet. And optical LIDAR sensors or computer vision enable the positioning of humans and machines, but are very demanding in terms of computing power and prone to errors in poor visibility.

The solution

Higher productivity with cobot radar sensors

Our radar sensors offer the reliability required for human-robot collaboration – even in the most adverse environments with dirt, smoke, fire or steam. These properties are also used for autonomous driving to ensure safety in demanding conditions such as rain, fog or backlight. Smart motion radar sensors based on modern network technology and artificial intelligence can detect human movements in production environments with collaborative robots (cobots) featuring a measuring precision in the micrometer range. Since radar waves radiate non-conductive materials, people can also be identified behind objects - e.g. if they are partially covered when carrying boxes or large packaging. The OndoSense radar sensors are interconnected to each other via the OndoNet sensor software: This ensures a spatial motion detection in all directions (360-degree coverage). In addition, the static protection zones previously required in the area of ​​industrial robots can be significantly reduced in real time by situation analysis. This allows the robot to continue working as long as people are not in immediate danger areas. The result: a productivity gain of up to 50 percent.

Real-time situation analysis for cobots. ©ipopba - Adobe Stock
OndoSense radar sensor solutions

Products & solutions

OndoSense apex – highly precise, relliable smart motion radar sensor

OndoNet software – cloud-based sensor control and networking, KI algorithms for situation analysis and human recognition

Industry range

Automotive industry

Electrical industry

Plant and mechanical engineering

Metal industry

 

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.