HD Hyundai XiteSolution wins KRW 6.33bn state project to train autonomous excavators in simulation
HD Hyundai XiteSolution, the holding company of HD Hyundai's construction equipment arm, said on Oct 25 it was selected for a KRW 6.33 billion project of Korea's trade and industry ministry (MOTIR) to build a high-fidelity digital twin in which AI-driven unmanned excavators, wheel loaders and articulated dump trucks can be designed, trained and tested before they reach a site. The consortium runs to December 2029.
HD Hyundai XiteSolution, the intermediate holding company that owns HD Hyundai Construction Equipment and HD Hyundai Infracore, said in a press release on Oct 25 that it had been chosen as a final participant in a project of Korea's trade and industry ministry (MOTIR) to build a high-precision, simulation-based digital twin platform for AI-driven unmanned autonomous excavators. The project carries a total budget of KRW 6.33 billion and runs until December 2029.
The platform is meant to reproduce in software how a machine actually behaves: its hydraulics, multibody dynamics and powertrain, and the way the bucket and tracks interact with soil. On that basis the consortium wants excavators, wheel loaders and articulated dump trucks to be designed, their autonomy software trained and their field behaviour checked in a virtual environment first. XiteSolution said its share of the work is to set the standard specifications for the parts database used in simulation and to run field validation and operating-scenario evaluation, feeding in data from its own machines. Its partners are Simji, Korea's construction-machinery research institute, the Korea Institute of Industrial Technology (KITECH) and the Korea Construction Equipment Manufacturers Association.
The company named the reason plainly: testing unmanned machines across many real job sites is slow and risky, so the project wants autonomy proven in simulation and then compared against data from real equipment. Kwak Sung-kyu, the executive in charge of virtual technology, said the company would help bring unmanned autonomy into mass production.
Why it matters
Earthmoving is where autonomy money has gone outside factories. MEKAWIRE's database holds the USD 225 million SoftBank is providing to ASI through a joint venture for autonomous heavy equipment, as reported in September, and USD 97 million that Built Robotics disclosed across two rounds for retrofitting excavators. Korea's contribution through this project is small by comparison and goes to an incumbent manufacturer, which matches the pattern in our review of Korea's physical-AI programmes: of KRW 444.9 billion in verified awards, most went to established makers. The KRW 6.33 billion here equals about 1.4% of that total.
- HD Hyundai XiteSolution consortium
- KR
- KRW 6.33bn
- Government R&D project to Dec 2029
- Oct 2026
- ASI (Autonomous Solutions)
- US
- USD 225m
- SoftBank funding via a joint venture (reported)
- Sep 2026
- Built Robotics
- US
- USD 97m
- Series B (USD 33m) and Series C (USD 64m)
- 2019 and 2022
Disclosed figures from primary sources stored in MEKAWIRE's database; not converted, not estimated.
As of Oct 26, 2026
The second signal is regulatory. Korea's land ministry launched a construction robot forum on Oct 20 and promised legal groundwork for robots on building sites. A validated digital twin is the kind of evidence such rules tend to ask for. The open question is whether XiteSolution will share the platform with smaller equipment makers through the association, or keep it as an in-house tool for HD Hyundai's own machines.
- To December 2029
- KRW 6.33 billion total
- High-precision simulation-based digital twin platform for AI unmanned autonomous excavators (MOTIR)
- HD Hyundai press release, Oct 25, 2026
- HD Hyundai XiteSolution, Simji, Korea's construction-machinery research institute, KITECH, Korea Construction Equipment Manufacturers Association
- Excavators, wheel loaders, articulated dump trucks
- Standard specifications for the simulation parts database, field validation, operating-scenario evaluation
