RoboticsTomorrow.com Articles, Stories and Products

We asked TI experts to explain how semiconductor technologies could enable humanoid robots to move from specialized applications to scalable real-world systems, and what it will take to scale them for deployment.

One significant trend is the emergence of mixed-SKU depalletizing. As 3D vision systems continue to improve, robots will become increasingly capable of identifying and handling pallets containing different products, making this type of application more common.

Here, Nigel Smith, CEO of TM Robotics, Shibaura Machine’s official distribution partner for injection moulding machines and automation systems in the UK and Ireland, explains why processors must select moulding systems to handle a broader material mix.

Charging strategy, battery chemistry, and the electrical infrastructure behind them quietly determine whether a fleet delivers the throughput it promised or stalls when demand is highest.

Bulles Création built its business on flexibility, bottling for local winemakers while developing its own effervescent drinks. But as demand grew, the company's production tools couldn't keep up. Its packaging line was capped at 1,500 bottles an hour.

The Physical AI companies that will win in manufacturing aren’t the ones collecting the most data. They’re the ones that have figured out which data is worth generating, and built the organizational discipline to generate it effectively.

In this white paper, we’ll identify some scenarios and use cases where customization delivers meaningful value — helping you determine when standard drives suffice and when custom solutions justify the investment.

From a robotic arm delicately gripping an object to a conveyor system detecting product presence, every action begins with input signals. These signals translate physical conditions–such as position, force, temperature, or presence – into data a machine can process.

In total, the project included approximately 165,000 square feet of elevated platform structure and more than 21,000 square feet of grid structure supporting conveyor systems throughout the facility.

In these systems, the motion requirements are especially challenging because the payload is not fixed. As the arm extends, rotates, and dispenses material, the mechanical leverage changes continuously.

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maxon MIND was developed to take condition monitoring and predictive maintenance to a new level. The solution analyzes data read from the controller during machine operation and detects patterns that indicate wear or malfunctions.

The most effective automation systems preserve the simplicity and predictability of classic PLC control while selectively embracing modern tools where they add real value.

Solving real world challenges for long runtime for a battery powered AMR, multi megawatt peaks in a welding cell, or microsecond level responsiveness in a medical robot means engineering the power chain with the same rigor as the mechanical joints or control firmware.

Even microscopic contamination on a fibre connector end face can interfere with light transmission. In robotic applications where precision, repeatability and uptime are critical, small amounts of contamination can contribute directly to performance issues.

Robots are now more applicable for a wider range of warehouse tasks than ever before. Keep these trends and considerations in mind to make the right investments, achieve effective implementations, and realize the full business value of today’s robotic systems

It delivers groundbreaking AI acceleration, neural rendering and the headroom needed for today’s most demanding professional workflows powered by 5th Gen Tensor Cores, 4th Gen RT Cores and advanced NVIDIA® CUDA® cores.

This marks the first time an embodied AI humanoid robot has served as a full-scenario companion at a World Cup, signaling embodied AI's expansion from industrial and laboratory settings into one of the world's most celebrated sporting stages.

Supply chain automation will become more intelligent, connected, and adaptive. AI-driven software will continue evolving from reactive monitoring toward predictive and prescriptive capabilities that help operations rebalance workloads and automatically optimize performance.

The question is no longer only whether an AGV can follow a route reliably, but whether its navigation technology allows the robot to adapt as processes, layouts, and demands change.