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Slamcore, a spatial intelligence company that gives situational awareness to robots, drones, machines, and VR/AR headsets, has raised $16 million in a series A round of funding.
With the autonomous mobile robot market alone shaping up to be a $22 billion industry within a decade, Slamcore is betting that its AI-powered localization and mapping smarts will play a big part in powering the self-navigating machines of the future, be it drones, vacuum cleaners, or warehouse picking-and-packing systems.
Throw into the mix the burgeoning metaverse movement that leans heavily on virtual reality (VR) and augmented reality (AR) headsets, requiring humans and machines to map and navigate both real and virtual worlds simultaneously, and it’s clear that Slamcore is fairly well future-proofed.
“For far too long, robots have not been able to navigate physical spaces with the level of accuracy and efficiency that we know is possible,” Slamcore founder and CEO Owen Nicholson said in a press release. “As they become more available to companies and consumers alike in years to come, Slamcore is determined to ensure that as many designers as possible have access to the algorithms needed to optimize their products.”
Founded out of London in 2016, Slamcore has developed AI algorithms that serve to answer three main questions that a moving machine may need answered: Where am I in 3D space? What are the objects around me? And where are the objects around me?
In a busy warehouse, for example, myriad people and objects interact with each other, from pickers and packers to forklift trucks and pallets. Throwing autonomous machines into such an environment could cause real problems if these machines can’t figure out where everything is, and lead to major accidents. Thus, simultaneous localization and mapping — or SLAM, as it’s known in industry parlance — is a long-established computational problem focused on how to get autonomous systems to move around an environment without bumping into other things.
Generating accurate positional awareness in unmapped or fast-changing environments is no easy feat, particularly when indoors or in built-up areas where GPS is less effective. And that is the core problem that Slamcore is setting out to fix, by helping machines both map and move through new environments, using nothing more than data gathered from the machine itself to build maps of environments in real time.
So Slamcore, effectively, transforms sensor data from lidar, sonar, radar, and more, into a “real-time spatial understanding,” and delivers this to companies via a software development kit (SDK).
“We provide accurate, robust and commercially viable SLAM using affordable cameras and components that will benefit wide swathes of businesses and improve the user experience of consumer products,” Nicholson added.
While Slamcore is a software and AI company at its heart, it has to play close attention to the types of hardware that is used by companies operating in the robotics or AR/VR space — and so it says that it has optimized its algorithms “for some of the most widely used sensor and processor combinations,” allowing designers and developers to use Slamcore out-of-the-box with minimal configuration.
Prior to now, Slamcore had raised around $11 million, from big-name backers including Toyota’s venture capital fund, which has participated once more in the company’s latest fund round which was co-led by Robo Global Ventures and Presidio Ventures. Other participants included Samsung Ventures, Amadeus Capital, Global Brain, IP Group, MMC, Yamato Holdings, and Octopus.
With a fresh $16 million in the bank, Slamcore said that it’s well-financed to capitalize on its “proven technology” which has already been used in pilots by major companies including Facebook’s parent company Meta, which tapped Slamcore as part of its development of Bombyx, a robot that expedites fiber-deployment by climbing along electricity distribution lines
“This funding will allow us to rapidly scale to meet the demand from consumer electronics, logistics, industrial and manufacturing sector clients all keen to deploy low-cost, high accuracy SLAM at commercial scale,” Nicholson said.
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