At AIIM (AI in Motion) we enable reliable mobile autonomous solutions in open, dynamic and unconditioned environments by utilising state of the art artificial intelligence and core vision technologies. Through our extensive research, our neural networks portfolio ranks among the best in the world, including best real-time performance. Our current developments include Hybrid 3D localization solutions and deep learning 3D LiDAR based object detection and classification.
Our goal is to expand the level of automation in the selected sectors for the pioneering companies that embrace the use of AI technology. Our target markets are maritime, logistics, hospitality, agri-tech and new automotive. These sectors are searching for AI solutions which will prevent human faults and reduces costs as a result in the long term.
We were founded in February 2019 out of a discussion between Navinfo Europe and our CTO Gijs Dubbelman. Both of them realized that a revolution is happening within localization and mapping technology by mixing this with the latest research on machine learning. As such we’ve concluded that the best way forward was to combine both channels of advanced research into products which add value to automated guided vehicles and robots in motion. Resulting in the birth of our start-up AIIM. We see a lot of opportunities to improve the quality of service and reducing costs within the development of such self-driving machines. And in markets such as maritime which so far have a more conservative approach when it comes to automation, we are happy to bring in our know-how and experience from our comfort zone: the automotive market.
One of our current projects consists of a solution that can be used to localize itself purely by using LiDAR. This solution consists of a computation box, together with either a single or multiple LiDAR sensors, depending on the use case. It can be applied in any location that we can map with our mapping vehicle. Our system will then allow the customer vehicle to localize itself with millimetre accuracy all over this map. This gives it an advantage over regular positioning techniques such as transponders and GNSS. It costs a lot less to cover a large area compared to transponders. It also suffers less than GNSS from tree cover, large surrounding buildings, or going indoors. This makes it a good all-round localization product that is flexible to its application.
AI in Motion | AIIM
5657 EB Eindhoven