Intralogistics 5.0 leverages automated material handling, Internet of Things (IoT), data analytics, and Artificial Intelligence (AI) to create smart, interconnected, data-driven production environments and empower human workers.
Exploring the concepts of AI, Visual AI, Machine Learning, and Deep Learning and the way Sevensense leverages these technologies as part of its offering beyond Visual SLAM
Limitations of legacy automation technologies are setting the logistics industry back. The Sevensense Visual SLAM solution is optimal for dynamic spaces and can easily be integrated into any vehicle platform, giving their manufacturers access to the 94% of warehouses currently untapped by automation.
We say vision is the future of mobile robotics, but why? It’s because we’ve found that vision combined with inertial sensing and AI sensor fusion uniquely enables mobile robots to do what people do every day: autonomously sense their surroundings as they move through them, map them out intelligently, and localize themselves within that map. With Alphasense Position we are bringing vision and all its advantages to the market.
The DARPA-funded Subterranean “SubT” robotics challenge has set out to revolutionize autonomous exploration operations in the underground domain. The winning team, CERBERUS, used legged and aerial robots to tackle the harsh underground environments.
Sebastian joined Sevensense in 2019, after completing his Master's degree in mechanical engineering at ETH Zurich. With his experience in engineering and programming, he knows how to come up with the best algorithms for our robots. He is a valued member of the Localization Team, where he helps our robots with one of their most important tasks: understand their own position in the environment where they operate.
How does a world with robots look like and what role does Sevensense play in this development? Together with our team member Roland Siegwart we discussed exciting questions about the future of robotics!
Self-localization is essential for robots to safely navigate in changing environments and achieve full autonomy. By employing cameras for this task together with smart algorithms for building and maintaining maps, autonomy can be provided at a fraction of the costs - be it for the sensor gear itself, as well as operating costs over the robot’s lifetime.
Miguel joined Sevensense in September 2018, being the first employee. With his experience in autonomous racing and the control industry he knows what it takes to make robots work. He initially worked in the planning and control team developing our navigation stack. In 2020 he moved to lead the robotic systems team where he helps our technology shine in our customers robots.
Common mobile robots in industry or logistics use 2D laser rangefinders. These 2D LiDARs output very little information about the surroundings - it is sufficient to detect an obstacle at a certain location, but not enough to understand what it is exactly and how to react in a smart way.
At Sevensense, we consider company culture to be something very important. That's why we have initiated some efforts to strengthen it in our company.
Dina joined Sevensense in August 2019 after she completed her PhD in Robotics at the University of Girona in Spain. Now, she is a valued engineer and member of the Planning & Control Team, where she takes care of one of the most challenging tasks at Sevensense: Ensuring that our robots can move and avoid obstacles!