At CES 2026, the robotics dialog has quietly shifted. Fewer persons are asking whether or not robots can transfer sooner or raise heavier objects. More are asking one thing tougher: why are robots nonetheless struggling exterior managed demos — and what’s lacking to make them dependable in the actual world?
For many within the business, the reply is information. Not artificial information or scripted motions, however actual interplay information that captures how objects behave when they’re touched, pushed, squeezed, or moved.
That’s the issue Daimon Robotics is making an attempt to handle with the DM-EXton2, a teleoperation-based information acquisition system unveiled at CES this yr. It isn’t a shopper product. It’s knowledgeable instrument designed to assist robots study from human interplay at scale.
Robots aren’t dumb — they’re inexperienced
Recent advances in AI have dramatically improved notion, language understanding, and reasoning. But bodily interplay stays a weak level. A robotic might acknowledge an object completely and nonetheless fail when requested to choose it up, insert it or manipulate it safely.
The cause is easy: the bodily world is messy. Force, friction, deformation and speak to change from second to second and people alerts are tough to seize cleanly. Most robots merely haven’t seen sufficient of this information.
Traditional information assortment strategies include trade-offs. Dedicated seize environments are costly and labor-intensive, but nonetheless produce restricted reusable information. Simulation is cheaper, however the hole between digital physics and actuality typically results in fashions that work within the lab and fail in observe.
Worse, many current techniques intrude with the very conduct they’re making an attempt to file. Bulky tools restricts pure motion, whereas restricted sensing misses the refined drive and tactile cues people depend on instinctively.
Alex Tchaikovsky / Digital Trends
What a robotic information acquisition system really does
A teleoperation-based information acquisition system approaches the issue in a different way.
Building on conventional teleoperation approaches, a teleoperation-based information acquisition system information interplay information in actual time with higher consistency throughout a number of alerts. A human operator remotely controls a robotic to carry out actual duties — greedy objects, inserting parts, or manipulating instruments — whereas the system captures movement, timing, contact, and drive information concurrently.
In impact, the robotic learns by watching and feeling how a human does the job. The nearer this setup is to pure human conduct, the extra helpful the ensuing information turns into.
Built for real-world information, not demos
The DM-EXton2 is the world’s first haptic-feedback teleoperation system for robotic information acquisition, designed to seize high-quality interplay information from real-world duties.
It is designed round responsiveness and deployment flexibility slightly than wearable specs. Operating at a 1000Hz response price, the system permits millisecond-level command synchronization that helps clean, low-latency teleoperation throughout information assortment.
It additionally helps full-body teleoperation, together with coordinated management of cell bases and waist joints, increasing the vary of duties that may be captured. Together with adaptive movement scaling and fast end-effector switching, these capabilities enable a single system to assist each nice manipulation and large-range actions with out interrupting the data-collection course of.
To accommodate completely different working environments, the DM-EXton2 is obtainable in two configurations: a backpack model suited to cell data-collection setups, and a stand-mounted model designed for fastened workstations. This permits operators to decide on the format that most closely fits their workflow, whether or not information is being captured throughout dynamic areas or inside secure, repeatable environments.
Daimon Robotics
Putting drive and tactile into the loop
Where the DM-EXton2 stands out most is in pairing operator-side drive suggestions with tactile sensing for information assortment.
The system brings these drive capabilities right into a broader teleoperation framework, enabling extra pure and exact manipulation throughout information assortment. As the robotic interacts with its atmosphere, contact forces are fed again to the operator in actual time. Tasks like dealing with fragile objects or performing exact insertions grow to be extra intuitive, even when the robotic’s view is partially obstructed.
This isn’t nearly enhancing the operator’s management expertise. At the robotic degree, drive and tactile alerts are recorded alongside movement information, creating multimodal datasets that mirror how people really work together with objects. That information is vital for educating robots not simply how one can transfer, however how one can choose contact and adapt to bodily constraints.
From remoted experiments to repeatable studying
By synchronizing movement, drive, and contact, the DM-EXton2 acts as a bridge between human talent and machine studying. Human instinct turns into structured information that robots can study from, reuse, and apply throughout duties.
That shift issues. Instead of amassing small, task-specific datasets, groups can construct ongoing pipelines for information era. Over time, this helps sooner mannequin coaching and extra dependable deployment.
Closing the loop
The system additionally matches right into a broader change in how robots are developed. Data assortment, mannequin coaching and deployment are now not separate levels. They more and more type a loop.
High-quality interplay information feeds into multimodal fashions — together with Vision-Tactile-Language-Action frameworks — which enhance robotic conduct. Real-world use then generates new information that refines the subsequent coaching cycle.
For that loop to work, information has to maneuver freely. Standardization and compatibility aren’t nice-to-haves; they’re stipulations.
Alex Tchaikovsky / Digital Trends
Where Daimon Robotics matches in
Daimon Robotics focuses on the applied sciences that assist robotic studying, slightly than constructing full robots. Its work spans tactile sensing, dexterous manipulation {hardware}, and teleoperation techniques designed to assist large-scale information assortment.
The firm was incubated on the Hong Kong University of Science and Technology and based by Professor Yu Wang, founding director of the HKUST Robotics Institute, together with Dr. Jianghua Duan. The group combines tutorial analysis with expertise in deploying robotics expertise past the lab.
Within this method, the DM-EXton2 serves as a key element of Daimon Robotics’ “3D” technique — Device, Data, and Deployment. Drawing on the corporate’s long-term give attention to tactile sensing and dexterous manipulation, the system helps flip drive and contact information into usable inputs for superior studying fashions, supporting progress towards extra general-purpose robotic functionality.
Why this issues
As robots transfer nearer to on a regular basis environments, progress will rely much less on intelligent algorithms and extra on whether or not machines can study from the bodily world they function in.
The DM-EXton2 doesn’t promise immediate autonomy. Instead, it serves as a vital bridge, enabling robots to be guided by means of real-world duties in order that high-quality interplay information could be captured as a basis for extra normal capabilities.
You can study extra about Daimon Robotics by way of its firm web site, LinkedIn profile and YouTube account.