iNews24 Highlights Haply’s Approach to Physical AI and Robot Learning

iNews24 featured Haply Robotics in its CES 2026 coverage of technologies advancing the next generation of robot AI.

The article discussed Haply alongside Maum AI, with each company representing a different part of the Physical AI ecosystem.

Maum AI’s work focused on helping robots interpret information, process instructions, and plan actions. Our work focused on how haptic technology can help capture the physical information involved in completing a task.

Intelligence must become physical action

AI systems can interpret images, process language, and generate plans.

A robot, however, must convert those plans into physical movement. It needs to reach the correct location, make contact with an object, and apply an appropriate amount of force.

This distinction is central to Physical AI.

An instruction such as “pick up the object” may be easy for a person to understand. Carrying it out requires physical decisions that depend on the object’s size, weight, material, stability, and surrounding environment.

The robot must learn not only the desired outcome, but also the physical behaviour required to achieve it.

The role of imitation learning

Imitation learning allows robots to learn from human demonstrations.

A person performs a task, and the system records information that can help the robot reproduce it. Movement data can show the path followed and how the task progressed over time.

However, movement alone may not explain the complete interaction.

For example, a demonstration may show a tool following the correct path without revealing how firmly the user pressed, when resistance occurred, or how force changed during the task.

Our haptic technology can add this missing physical context.

HARP and human-guided robot learning

iNews24 highlighted our Human Advanced Robotics Platform, HARP, following its CES 2026 Innovation Awards recognition.

We designed HARP to help robotics teams connect human movement, force feedback, and robot-control workflows.

Using our haptic interfaces, an operator can guide an interaction while the system captures information about movement and physical forces.

• Human-guided robot demonstrations

• Imitation learning

• Teleoperation

• Force-aware data collection

• Simulation

• Robot workflow development

By capturing more than visual movement alone, our haptic systems can help teams build a more complete representation of how a physical task is performed.

Combining simulation with physical interaction

Simulation is increasingly important in robotics because it gives teams a controlled environment in which to develop, test, and repeat interactions.

Our work with the NVIDIA robotics ecosystem connects haptic interaction with simulation tools such as NVIDIA Isaac Sim.

Within a compatible simulated environment, an operator can guide a robotic interaction through a Haply interface while receiving force feedback from the virtual system.

This can help teams develop and evaluate human-guided workflows before or alongside deployment on physical robots.

Simulation does not eliminate the need for real-world testing. It provides another environment in which researchers can build, repeat, and improve the interaction.

Different technologies solving connected problems

The original iNews24 article discussed Maum AI and Haply because we represent different layers of robot intelligence.

AI systems can help robots interpret requests and determine what action to take. Haptic and demonstration technologies can help capture how that action should be performed physically.

These capabilities are complementary rather than interchangeable.

The next generation of robots will depend on perception, language understanding, planning, simulation, robot control, touch, and human demonstration working together.

No single layer solves the entire Physical AI challenge.

Helping intelligent machines interact with the real world

Our role in Physical AI is centred on the physical connection between people, simulations, and robots.

By capturing movement and force, we help teams explore how human physical knowledge can become useful robotics data and repeatable workflows.

The iNews24 coverage recognized this as an important part of the broader evolution of robot intelligence.

Read the original iNews24 article

This page summarizes Haply’s inclusion in iNews24’s CES 2026 coverage of robot AI, imitation learning, and Physical AI technologies.

Original source

https://www.inews24.com/view/1926759

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