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Accurate real-time maps are essential for autonomous navigation. Knowing where objects are is critical to path planning and obstacle avoidance. Learn more in this blog.
Deputy Head of Research and Development, Tom Woodley, reflects on his career and time at SLAMcore.
The first of a three-part series that explores "Position" as part of the three levels of SLAM compatibility that form part of our full-stack algorithm.
As the use cases of XR become increasingly sophisticated, I set out to gain valuable insights into XR’s future.
Upon graduating, Cheryn wanted to make a difference - read more about how she turned her internship into a career which is shaping the future of robots and the metaverse.
Autonomous robots and XR headsets are proliferating the marketplace, but why aren't more robots around the home, workplace, or in critical and dangerous locations?
SLAMcore algorithms deliver spatialAI crucial to robots, spatially aware machines and devices working in physical world and Metaverse
The SLAMcore SDK has helped robots map and locate autonomously as they travel over five million metres.
SLAMcore AI neural network provides fast accurate depth completion at the edge supporting unsupervised training and rapid real-world deployment of robots
