Blog | Robotiq

In 2016, I said something that went against where robotics was heading at the time: vision alone doesn’t work for grasping. Not “it needs improvement.” Not “the tech isn’t there yet.” It doesn’t fit the problem. Grasping is physical. Contact, force, friction. Vision can guide the approach. It can’t feel what happens next. Back then, we saw it in the lab. Tactile vibration data predicted grasp fai…

Medra Lab 001 is the largest autonomous AI-driven laboratory in the United States, operating continuously with robotics, AI, and adaptive grippers. Medra Lab 001 never sleeps. It reads the literature, designs experiments, runs them, analyses the results, and decides what to try next — continuously, without a human at the bench. Built across 38,000 square feet in under 90 days , it is already runn…

Pharmaceutical manufacturers are under pressure to increase output, maintain strict compliance, and protect their workforce, all within tightly controlled environments. Yet many facilities still rely on manual palletizing at the end of the line, where variability and risk are hardest to control. As a result, more pharmaceutical manufacturers are adopting robotic palletizing as a standard part of …

Physical AI is advancing quickly. AI models can now recognize objects, plan actions, and adapt to new tasks. But despite this progress, most systems still struggle to scale in real-world environments. Two core challenges explain why: Limited real-world dexterity High cost and complexity of deployment Until these are solved, Physical AI will remain difficult to scale beyond controlled applications.

Artificial intelligence has made impressive progress. Models can classify images, generate text, and even plan complex sequences of actions. But when you take AI out of the digital world and place it into a factory, a warehouse, or any physical environment, something breaks. The AI can decide. But it can’t reliably act. This is the gap that defines Physical AI —and it’s where most real-world robo…

TIDI Products, a global manufacturer of infection prevention and patient safety products, transformed its end-of-line operations by automating with Lean Palletizing. The result: measurable gains in productivity, safer working conditions, and more efficient use of labor. This case shows how robotic palletizing can directly improve manufacturing performance with clear, repeatable results.

Physical AI is evolving quickly. From imitation learning to foundation models, robotics teams are making real progress toward systems that can adapt, generalize, and improve over time. But there’s a gap. Many of these systems work well in controlled environments… yet struggle when faced with the variability of real production. If you’re a robotics OEM, product leader, or engineering team, you’ve …

Whether you are getting started with collaborative robots or planning to expand automation projects in your factory, get to production faster with the Resource Center.

Across Italy and the DACH region, food manufacturers are facing the same reality: 📈 Increasing production demand 👷 Labor shortages and rising costs ⚠️ End-of-line processes limiting throughput And more often than not, the bottleneck isn’t where you think. 👉 It’s palletizing .

Martin Ray Winery, a historic wine producer based in California, modernized its bottling operations by implementing a robotic palletizing solution . Results at a glance: Reduced manual palletizing labor Improved bottling line efficiency Increased operational reliability Expected ROI within 18–24 months This case highlights how collaborative robotic palletizers can solve labor shortages and produc…

Artificial intelligence has brought enormous excitement to robotics. Robots can now walk, navigate complex environments, and perform tasks that seemed impossible only a few years ago. But there is a major gap between robot demonstrations and real industrial deployment . A robot that works in a controlled research environment is very different from a robot that operates reliably on a production li…

Automation rarely starts with a full factory transformation. More often, it begins with a single line. One challenge, one opportunity, one team ready to try something different. What matters is what happens next.

Artificial intelligence has dramatically improved how robots perceive the world . Computer vision allows robots to detect objects, recognize patterns, and navigate complex environments. Cameras help robots identify parts on a conveyor, locate packages in a bin, and avoid obstacles in warehouses. But when a robot needs to pick up an object , vision alone is not enough. To manipulate objects reliab…

Coffee production is growing worldwide. From roasted beans to capsules and pods, manufacturers are increasing output to meet rising demand. Capsule formats such as Dolce Gusto® and other single-serve systems continue to expand in both retail and food service. But while packaging technology has evolved quickly, many coffee plants still rely on manual palletizing at the end of the line . That’s bec…

Artificial intelligence is moving fast. Large language models can write emails, summarize reports, and generate software code in seconds. But when AI leaves the digital world and enters the physical one, progress slows down dramatically. Why? Because interacting with the real world is much harder than processing text or images. Robots don’t just need intelligence; they need reliable ways to touch…

Artificial intelligence is transforming robotics. Vision systems can identify objects, machine learning models can plan motions, and digital twins can simulate entire production environments. But for all the progress in AI, there is a moment where intelligence must leave the digital world and interact with reality. That moment happens at the gripper . In robotics, the gripper is often seen as a s…

Across many manufacturing facilities, one role remains surprisingly difficult to fill: palletizing. While production lines have become increasingly automated, the final step—stacking boxes onto pallets—often still relies on manual labor. Workers lift, turn, and stack products continuously to prepare shipments for transport. On the surface, palletizing may seem like a straightforward task. In real…

At the end of the production line, everything comes together. Boxes are sealed, labeled, and ready to ship. But before they leave the facility, they still need to be stacked onto pallets. For many manufacturers, palletizing is still done manually. Workers lift, turn, and stack boxes for hours at a time. While it may seem like a simple task, manual palletizing often becomes a bottleneck as product…

Beyerdynamic doubles production without expanding its factory Increasing output by 50% without adding floor space sounds unrealistic for most manufacturers. That was the exact objective inside the production facility of Beyerdynamic, a German manufacturer of professional audio equipment and headphones. Leadership set a four-year plan: raise factory productivity by 50% while maintaining the same f…

How Sennheiser increased PCB testing by 33% with a Robotiq 2F-85 gripper At Sennheiser Manufacturing USA in Albuquerque, precision is non-negotiable. Every week, the facility assembles 30,000 printed circuit boards (PCBs) that power 1,500 professional audio devices for the Americas and Asia. With 115 different PCB variants running through production, automation is essential to maintain throughput…