Daimler Truck subsidiary Torc Robotics has signed an agreement to acquire Algolux Inc for its award-winning intellectual property and expertise in the areas of computer vision and machine learning.
Algolux has been recognized for excellence in its field and has been named to the 2021 CB Insights AI 100 List of the world’s most innovative artificial intelligence startups. Torc has been working closely with the company for over a year on multiple perception concepts and methods for robustly improving object detection and distance estimation while evaluating synergies between the two companies. Robust perception technology is key to helping Torc’s autonomous system correctly identify objects in difficult visual conditions such as low light, fog, or inclement weather. Algolux software is currently operating on initial Freightliner Cascadia test vehicles in the U.S. and is being included in areas of Torc’s software development efforts.
“On the path to commercialization of our autonomous-ready Freightliner Cascadia, with Torc’s virtual driver, we never stop improving safety. We are convinced that Algolux with its perception capabilities can bring us one step closer to reach our goal to safely and reliably bring SAE Level 4 autonomous trucks into series production in the USA within this decade”, says Joanna Buttler, Head of Autonomous Technology Group at Daimler Truck AG commenting on the agreement.
Algolux is headquartered in Montreal, Canada, with offices in Palo Alto, CA, and Munich, Germany. The transaction will close after the parties complete various pre-closing activities, including any required approvals.
“This acquisition brings together Algolux’s end-to-end AI stack, from photons to behaviour, with Torc’s pioneering autonomous technology. Add in a tightly integrated OEM truck platform and you have a dream scenario,” said Felix Heide, Algolux CTO. “While many think of autonomous transportation as futuristic, this winning combination will help bring to market a commercially viable, safety-critical long- haul trucking application at scale.”
