GIM provides smart sensor fusion software for navigation and 3D mapping. The system is integrated to existing vehicles, including work machines and cars. It can also be attached to GIM's robots, enabling completely autonomous data gathering. These are some of the advantages of our tecnology:
- Low cost
- Large area coverage
- Real-time results
- Applicable to various environments
Our navigation technology is based on observing the natural environment, so artificial infrastructure is not needed.
GimNavi is always customized for customer's application. Examples of our customer cases include:
- Autonomous logistics robots in retail and industrial areas
- Autonomous mining machines
- Daily construction site progress monitoring and change detection
- Precise positioning in harbor areas
- Maintenance such as cleaning and grass cutting - area coverage tasks in general
- Farming, forestry and other outdoor non-road machine automation
GimNavi is a combination of software and sensors that are customized to suit your application. We can use existing sensors in your vehicle or provide a complete package.Please contact us for pricing and demos.
The core technology used in GimNavi is based on our staff's world-class research on the following topics:
First, our CEO Jari Saarinen has been one of the pioneers in the field of 3D localization and mapping for mobile robotics. He has developed and published multiple significant findings related to 3D SLAM based on Normal Distributions Transform (NDT) and has shown the superior computational cost and accuracy versus traditional methods. Currently, this research allows us to build large maps quickly and position robots within those maps with a centimeter accuracy.
Second, we master sensor fusion for localization. With the help of our propiertary sensor data filter, we are able to combine positioning information from various sources into one more accurate estimate, using e.g. GNSS, RTK, LIDAR, radar, IMU, wheel odometry or UWB beacons. The advantage is that we will be able to reliably estimate position even during the time when GPS or some of the other sources provide unreliable data. It gives us a significant advantage in cases where the surroundings are unknown and dynamic.