Humanoid says KinetIQ Ascend reinforcement learning approaches human-level dexterity - The Robot Report
Humanoid is building humanoid robots with the goal of becoming the No. 1 general-purpose industrial humanoid robotics company within two years. Founded by Artem Sokolov in 2024, it has more than 250 engineers, researchers, and innovators from top global tec...
Key takeaways
- The most recent wave of humanoid‑robot news shows the technology moving rapidly from prototypes to commercial deployments and large‑scale financing.
- In early July, Chinese firms UBTECH and Unitree Robotics announced new manufacturing and service hubs in the Tianjin Economic‑Technological Development Area, positioning the region as a hub for mass production, after UBTECH’s Walker S2 demonstrated autonomous battery swapping.
- In the United States, Agility Robotics confirmed a SPAC merger that will list the company as the only publicly traded pure‑play humanoid maker, building on its Digit deployments across nine customer sites including Amazon and Toyota.
- Meanwhile, Apptronik highlighted its dual‑mode Apollo platform—both legged and wheeled—and its plan to create public “Robot Parks” worldwide.
- In Europe, AGIBOT unveiled its A3 humanoid at a London conference and launched a robot‑as‑a‑service model for retail and hospitality use.
Humanoid is building humanoid robots with the goal of becoming the No. 1 general-purpose industrial humanoid robotics company within two years. Founded by Artem Sokolov in 2024, it has more than 250 engineers, researchers, and innovators from top global tech companies.
With offices in London, Boston, Vancouver, and San Diego, Humanoid said it is building commercially viable, scalable, and safe systems for real-world applications. In May, the company partnered with Bosch and Schaeffler to scale production of its HMND robots.
KinetIQ Ascend supports ‘capability factory’ The Robot Report
Humanoid says KinetIQ Ascend reinforcement learning approaches human-level dexterity
By The Robot Report Staff |
Arm drift after long reinforcement training caused by action prefix drift. Source: Humanoid
Robotic manipulation is making progress with artificial intelligence. London-based Humanoid last week introduced KinetIQ Ascend, its reinforcement learning, or RL, approach designed to reach 99.9% manipulation reliability at human speed and beyond.
“The humanoid race is becoming a question of scale, and real-world RL can be a core part of the answer,” stated Jarad Cannon, chief technology officer at Humanoid. “Robots that once required months of manual tuning are now outperforming human demonstrations within days.” Humanoid said the results demonstrated that KinetIQ Ascend shows a new way of developing robot capabilities, proving effective across a range of real-world operational tasks, from high-speed single-arm picking to complex bimanual handling.
KinetIQ Ascend also demonstrated that robot performance improves predictably as training time increases. It’s similar to how large language models (LLMs) improve as more compute and data become available. The company said that the observed scaling trend, supported by simulation experiments, suggests that its method scales all the way to 100% reliability.
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