EPFL researchers are developing robotic beehive frames that help locate honey stores inside of beehives over time, without relying on cameras. The aim is to develop new observation tools to study honeybee behavior that better fit the bees' natural way to occupy space compared to current methods.
EPFL researchers are developing robotic beehive frames that help locate honey stores inside of beehives over time, without relying on cameras. The aim is to develop new observation tools to study honeybee behavior that better fit the bees' natural way to occupy space compared to current methods.
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How Embedded Systems, AI, and Human-Centered Design Are Driving the Future of Robotics
Learn why teams still lose half their development time to test and fix, and what changes when you get real visibility into the target.
From simple sensor control to connected, intelligent devices, embedded systems often outgrow a single MCU. Pairing an MCU with Linux adds power and flexibility, but also introduces communication challenges, dual development workflows, and increasing software complexity.
This article explores how automated CI/CD pipelines replace fragile manual build processes with reproducible, auditable workflows that improve compliance, reduce defects, and accelerate development in regulated embedded systems
Mario Mauerer, maxon's Global Business Development Manager, Robotics, discusses what it takes for robotic deployments to be successful in complex real-world environments.
Join Prof. Fei Chen as he explores advanced bimanual manipulation and teleoperation techniques shaping the future of intelligent human-like robots in this expert-led robotics session.
'Link-bots' can move, explore, cooperate without sensing or computation
This article is part 4 of a 4-part article series on TDK's advanced robotics.
EPFL researchers are developing robotic beehive frames that help locate honey stores inside of beehives over time, without relying on cameras. The aim is to develop new observation tools to study honeybee behavior that better fit the bees' natural way to occupy space compared to current methods.
3 minutes read
Neural Jacobian Fields, developed by MIT CSAIL researchers, can learn to control any robot from a single camera, without any other sensors.
Learn more about how UWB is evolving, how Matter's standardization is enabling scalable ecosystems, and why Qorvo's partnerships and secure SoC platforms make it a leading player in the future of intelligent connectivity.
Did you miss ATCx AI for Engineers 2025? Catch up on key insights, real-world AI use cases, and how the event showcased AI's growing role in transforming engineering workflows, design, and smart manufacturing.
Researchers are shortcutting complex equations with AI, paving the way for engineering and scientific breakthroughs.
The CodeSteer system could boost large language models' accuracy when solving complex problems, such as scheduling shipments in a supply chain.
Batteries have long been the Achilles' heel of IoT solutions. When a battery dies, it often drags the entire solution down with it. Ambient IoT might be the solution.
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Smart micromobility operators pair fleet management platforms with connectivity infrastructure to gain better insights into vehicle performance and more effectively manage their fleets as a whole.
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MIT engineers designed a versatile interface that allows users to teach robots new skills in intuitive ways.
Texas A&M researchers received a grant from the U.S. Army Research Laboratory to address the limitations of applying artificial intelligence tools in military scenarios.
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OUTDATED ELECTRICITY METERING means a comparative lack of efficiency, accuracy, and even grid reliability. This not only places pressure on the bottom line for utilities but directly impacts the everyday lives and budgets of communities and households desperate for stable yet affordable power.
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Article #6 of Confronting AI Series: AI's rapid evolution has outpaced regulation. In this Q&A, Jared Bowns explores how adaptive frameworks, accountability, and ethical oversight can help engineers manage the risks and responsibilities of building trustworthy AI systems.
Article #5 of Confronting AI Series: Smart ML on embedded systems demands efficiency under tight memory, compute, and latency constraints. Techniques like pruning, quantization, low-rank decomposition, and federated learning enable compact, fast, and reliable models for edge intelligence.
The PhysicsGen system, developed by MIT researchers, helps robots handle items in homes and factories by tailoring training data to a particular machine.
This summer, EPFL and ETH Zurich will release a large language model (LLM) developed on public infrastructure. Trained on the "Alps" supercomputer at the Swiss National Supercomputing Centre (CSCS), the new LLM marks a milestone in open-source AI and multilingual excellence.
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