South Korea's KAIST Humanoid v0.7 robot showcases impressive moonwalk and soccer abilities, highlighting its precise high-speed locomotion, utilizing Physical AI for autonomous action in real-world environments. Developed at the DRCD Lab, the robot features custom-designed components, a Quasi-Direct Drive architecture, and can run at speeds up to 7.3 mph, climb steps over 12 inches.
A field test video depicts South Korea’s KAIST Humanoid v0.7 robot outstanding moonwalk and soccer skills, thus highlighting its precise high-speed locomotion.The 165-lb humanoid was developed at the Dynamic Robot Control & Design Laboratory , at the Korea Advanced Institute of Science and Technology , under the leadership of Hae-Won Park, PhD.
The clip highlights the humanoid’s use of Physical AI, an approach which enables autonomous machines to perceive, interpret, and execute complex actions in real-world environments. It can be seen running, jumping, taking shots on goal, and performing fluid dance movements on a soccer pitch. According to the research team, the five-foot-five-inch robot combines advanced hardware with intelligence control systems. It is designed to be reliable, efficient and scalable. Physical AI in actionInstead of relying on off-the-shelf-parts, the Korean researchers independently developed all of v0.7’s components, including the motors, gearboxes and motor drivers, thus making it technically independent. This made it possible to optimize torque density and power-to-weight ratios. As per the team, both are critical for high-speed locomotion and dynamic balance.At the same time, the robot’s actuation system is based on a Quasi-Direct Drive architecture. It pairs high-torque motors with low gear ratios, and boosts responsiveness while enabling more precise control. This is supported by a custom-designed 3K compound planetary gearbox, which achieves high gear reduction in a compact, single-stage configuration. It results in a lighter, more efficient system capable of handling demanding tasks like running, jumping and rapid directional changes.Hae-Won Park emphasized that the robot can run at speeds of up to 10.7 feet per second on flat ground. It can also climb steps over 12 inches high.“The team plans to further enhance its performance, aiming for a driving speed of 4.0 m/s , ladder climbing, and over 40-centimeter step-climbing capability,” Park said. What’s more, the humanoid’s knee actuator can deliver up to 320 Newton-meters of peak torque. Meanwhile, the ankle actuator is optimized for fast response and stability. This allows the system to perform complex movements with both strength and finesse.A powerful softwareTo produce smoother and more natural behavior, the researchers integrated deep reinforcement learning with human motion data. They trained the system in simulation and used human movement as a behavioral prior. This is how v0.7 can avoid the jerky motions often seen in purely AI-driven systems. It also incorporates Motor Operating Region modeling, which constrains the simulation to match the physical limits of the hardware, and adopts a hybrid approach known as modular residual learning. “This achievement is an important milestone that has achieved independence in both hardware and software aspects of humanoid research by securing core components and AI controllers with our own technology,” Park said.The robot can also navigate uneven terrain using proprioception alone, without relying on visual sensors. This is particularly relevant for industrial environments where visibility may be limited.“We will further develop it into a complete humanoid including an upper body to solve the complex demands of actual industrial sites and furthermore, foster it as a next-generation robot that can work alongside humans,” Park concluded in a press release. The DRCD Lab is meanwhile developing DynaFlow, a framework aimed to enable robots to learn complex tasks directly from human demonstrations. It could allow humanoids to perform practical jobs, from handling tools to operating machinery.
Humanoid Robot KAIST Physical AI Robotics Locomotion
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