Skip to content

Companies and products

Holiday Robotics

Updates on Holiday Robotics's robotics products, models, research, funding, applications, and partnerships.

3 selected · 0 in the last 30 days

  1. Holiday Robotics ·

    Holiday Robotics's FlashSAC Paper Wins RSS 2026 Best Paper Award, a First for a Korean Team

    A paper by Holiday Robotics researchers won the Best Paper Award at RSS 2026, a first for a Korean team. Its FlashSAC is a reinforcement learning algorithm that shortens humanoid robot walking training from several hours to a few minutes, overcoming the trade-off between learning speed and stability.

  2. Holiday Robotics ·

    Holiday Robotics raises KRW 155 billion Series A, largest in Korea

    Humanoid robotics startup Holiday Robotics announced on the 13th that it has closed a KRW 155 billion Series A round, the largest single-round investment for a Korean startup Series A and for a humanoid robotics company. The funds will be used to upgrade its mass-production system, expand its R&D team to more than 100 people, and build manufacturing infrastructure with annual capacity of more than 10,000 units. Its humanoid robot FRIDAY targets repetitive tasks in manufacturing, with commercialization planned for the second half of this year, production capacity of 100 units per year by 2026 and 1,000 units by 2027, and a near-term goal of lowering the product price to about KRW 100 million.

  3. Holiday Robotics ·

    South Korea's Ministry of Science and ICT Launches Physical AI Leading Technology R&D Project, Investing 34 Billion Won Over Two Years to Advance World Model Localization

    South Korea's Ministry of Science and ICT held a launch briefing for the Physical AI Leading Technology R&D Project in Seoul on June 9, planning to invest 34 billion won over two years to jointly develop a Korean-style world model and domestic simulator with 10 industry-academia-research institutions including LG Electronics, aiming to raise robots' final action success rate by more than 20 percentage points compared with not using a world model, and planning to achieve an MVP within one year and eight months and conduct validation at manufacturing and logistics sites.