CES 2026 and the move toward wearable robots you don’t wear all day.
Updated
January 13, 2026 10:56 AM
The π6 exoskeleton from VIGX. PHOTO: VIGX
CES 2026 highlighted how robotics is taking many different forms. VIGX, a wearable robotics company, used the event to introduce the π6, a portable exoskeleton robot designed to be carried and worn only when needed. Unveiled in Las Vegas, the device reflects a broader shift at CES toward robotics that move with people rather than staying fixed in industrial or clinical settings.
Exoskeletons have existed for years, most commonly in controlled environments such as factories, rehabilitation facilities and specialised research settings. In these contexts, they have tended to be large, fixed systems intended for long sessions of supervised use rather than something a person could deploy on their own.
Against that backdrop, the π6 explores a more personal and flexible approach to assistance. Instead of treating an exoskeleton as permanent equipment, it is designed to be something users carry with them and wear only when a task or situation calls for extra support.
The π6 weighs 1.9 kilograms and folds down to a size that fits into a bag. When worn, it sits around the waist and legs, providing mechanical assistance during activities such as walking, climbing or extended movement. Rather than altering how people move, the system adds controlled rotational force at key joints to reduce physical strain over time.
According to the company, the device delivers up to 800 watts of peak power and 16 Nm of rotational force. In practical terms, this means the system is designed to help users sustain effort for longer periods, especially during physically demanding activities_ by easing the body's load rather than pushing it beyond normal limits.
The π6 is designed to support users weighing between 45 kilograms and 120 kilograms and is intended for intermittent use. This reinforces its role as a wearable companion — something taken out when needed and set aside when not — rather than a device meant to be worn continuously.
Another aspect of the system is how it responds to different environments. Using onboard sensors and processing, the exoskeleton can detect changes such as slopes or uneven ground and adjust the level of assistance accordingly. This reduces the need for manual adjustments and helps maintain a consistent walking experience across varied terrain, with software fine-tuning how assistance is applied rather than directing movement itself.
The hardware design follows a similar logic. The power belt contains a detachable battery, allowing users to remove or swap it without handling the entire system. This keeps the wearable components lighter and makes the exoskeleton easier to transport. The battery can also be used as a general power source for small electronic devices, adding a layer of practicality beyond the exoskeleton’s core function.
VIGX frames its work around accessibility rather than industrial automation. “To empower ordinary people,” said founder Bob Yu, explaining why the company chose to focus on exoskeleton robotics. “VIGX is dedicated to expanding the physical limits of humans, enabling deeper outdoor adventures, making running and cycling easier and more enjoyable and allowing people to sustain their outdoor pursuits regardless of age.”
Placed within the wider context of CES, the π6 sits alongside a growing number of portable robots and wearable systems that prioritise convenience, mobility and personal use. By reducing the physical and practical barriers to wearing an exoskeleton, VIGX is testing whether assistive robotics can move beyond niche environments and into everyday life. If that experiment succeeds, wearable robots may become less about dramatic augmentation and more about quiet support — present when needed and easy to put away when not.
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Robots that learn on the job: AgiBot tests reinforcement learning in real-world manufacturing.
Updated
January 8, 2026 6:34 PM
A humanoid robot works on a factory line, showcasing advanced automation in real-world production. PHOTO: AGIBOT
Shanghai-based robotics firm AgiBot has taken a major step toward bringing artificial intelligence into real manufacturing. The company announced that its Real-World Reinforcement Learning (RW-RL) system has been successfully deployed on a pilot production line run in partnership with Longcheer Technology. It marks one of the first real applications of reinforcement learning in industrial robotics.
The project represents a key shift in factory automation. For years, precision manufacturing has relied on rigid setups: robots that need custom fixtures, intricate programming and long calibration cycles. Even newer systems combining vision and force control often struggle with slow deployment and complex maintenance. AgiBot’s system aims to change that by letting robots learn and adapt on the job, reducing the need for extensive tuning or manual reconfiguration.
The RW-RL setup allows a robot to pick up new tasks within minutes rather than weeks. Once trained, the system can automatically adjust to variations, such as changes in part placement or size tolerance, maintaining steady performance throughout long operations. When production lines switch models or products, only minor hardware tweaks are needed. This flexibility could significantly cut downtime and setup costs in industries where rapid product turnover is common.
The system’s main strengths lie in faster deployment, high adaptability and easier reconfiguration. In practice, robots can be retrained quickly for new tasks without needing new fixtures or tools — a long-standing obstacle in consumer electronics production. The platform also works reliably across different factory layouts, showing potential for broader use in complex or varied manufacturing environments.
Beyond its technical claims, the milestone demonstrates a deeper convergence between algorithmic intelligence and mechanical motion.Instead of being tested only in the lab, AgiBot’s system was tried in real factory settings, showing it can perform reliably outside research conditions.
This progress builds on years of reinforcement learning research, which has gradually pushed AI toward greater stability and real-world usability. AgiBot’s Chief Scientist Dr. Jianlan Luo and his team have been at the forefront of that effort, refining algorithms capable of reliable performance on physical machines. Their work now underpins a production-ready platform that blends adaptive learning with precision motion control — turning what was once a research goal into a working industrial solution.
Looking forward, the two companies plan to extend the approach to other manufacturing areas, including consumer electronics and automotive components. They also aim to develop modular robot systems that can integrate smoothly with existing production setups.