KAIST

“RAIBO”, KAIST’s four-legged robot featuring remarkable agility even on challenging terrains like sandy beaches, is now set to be the first in the world to complete a full marathon.

< Photo 1. A group photo of the research team of Professor Je Min Hwangbo (second from the right in the front row) of the Department of Mechanical Engineering who participated in the marathon event at 2024 Geumsan Insam Festival last September >

On the 17th of November, KAIST (represented by President Kwang Hyung Lee) announced that Professor Je Min Hwangbo’s team from the Department of Mechanical Engineering has developed an upgraded version, “RAIBO2,” which will take on the full 42.195-kilometer course at the "Sangju Dried-Persimmon Marathon".

This is over double the previous maximum distance achieved by quadruped robots, which was limited to around 20 kilometers. The KAIST team has successfully developed a robot that can walk continuously for 43 kilometers on a single charge, completing the course in 4 hours and 40 minutes by following a GPS-guided path on the university’s main athletic field. Through this marathon, the team aims to demonstrate RAIBO2’s walking performance in an actual urban environment.

Previously, most measurements of walking robots’ travel distances were confined to controlled laboratory conditions or theoretical data. This marathon challenge is thus significant in that the robot will run alongside the general public in a real urban setting, marking the first attempt to validate the practical potential of four-legged robots in real environments. 

Quadruped robots have shown advantages in challenging terrains, such as ice, sand, and mountainous areas, where they can walk stably. However, limited travel distance and running time have long been obstacles to wider applications.

< Figure 1. Conceptual diagram of power flow employed by the quadruped robot >

Professor Hwangbo’s team designed every component of the robot, from its actuators to its mechanical structure, to overcome these limitations. Notably, they implemented an efficient walking control system based on reinforcement learning using their proprietary dynamic simulator “RaiSim”.

The team also collected and analyzed walking data from outdoor environments, creating a model to address walking losses. This model was then used to iteratively improve walking efficiency over one full year.

< Figure 2. The leg posture change process of RAIBO2 walking at the most efficient walking speed of 3 m/s. By reducing the ground contact speed of the feet, the collision energy loss was reduced, and by minimizing the slipperiness of the foot upon contact, the body's kinetic energy was maintained towards the direction of the movement. >

This is the team’s second attempt. Their first was during the marathon event at “Geumsan Insam Festival” in September when the robot’s battery ran out at the 37-kilometer mark, falling short of completion. The battery drained 10 kilometers earlier than expected due to frequent speed changes as the robot adjusted to the pacing of other runners on the course.

Following the initial attempt, the team focused on technical improvements for a successful finish. They enhanced control efficiency by implementing joint stiffness control directly onto the motor actuator and increased battery capacity by 33% by refining the internal structure. These improvements enabled the robot to cover a maximum distance of 67 kilometers on straight paths.

< Figure 3. Data from completing 43 km on a single charge at the main sports field on campus. Left) GPS data of the driving course used during autonomous running. Middle) Covered distance by the hour. Right) Energy consumption by module >

Choongin Lee, a Ph.D. student of RAI Lab who is one of the co-first author of this study, explained, “Our comprehensive analysis of walking losses in terms of mechanics, electrical systems, and walking methods was crucial to improving walking efficiency. This research marks an important milestone in extending the operating range of quadruped robots to urban environments.”

< Photo 2. A Photo from Practice Run>

This research was supported by the Samsung Electronics Future Technology Development Center and RAION ROBOTICS Co., Ltd.