ΑΙhub.org
 

Bipedal robot developed at Oregon State learns to run


by
11 August 2021



share this:

Cassie the robotImage courtesy of Jonathan Hurst, Oregon State University.

By Steve Lundeberg

Cassie the robot, invented at Oregon State University and produced by OSU spinout company Agility Robotics, has made history by traversing 5 kilometres outdoors in just over 53 minutes. The robot was developed under the direction of robotics professor Jonathan Hurst with a 16-month, $1 million grant from the Advanced Research Projects Agency of the U.S. Department of Defense.

Since Cassie’s introduction in 2017, OSU students funded by the National Science Foundation have been exploring machine learning options for the robot.

“The Dynamic Robotics Laboratory students in the OSU College of Engineering combined expertise from biomechanics and existing robot control approaches with new machine learning tools,” said Hurst, who co-founded Agility in 2017. “This type of holistic approach will enable animal-like levels of performance. It’s incredibly exciting.”

Cassie, with knees that bend like an ostrich’s, taught itself to run with what’s known as a deep reinforcement learning algorithm. Running requires dynamic balancing – the ability to maintain balance while switching positions or otherwise being in motion – and Cassie has learned to make infinite subtle adjustments to stay upright while moving.

“Cassie is a very efficient robot because of how it has been designed and built, and we were really able to reach the limits of the hardware and show what it can do,” said Jeremy Dao, a Ph.D. student in the Dynamic Robotics Laboratory.

“Deep reinforcement learning is a powerful method in AI that opens up skills like running, skipping and walking up and down stairs,” added Yesh Godse, an undergraduate in the lab.

Hurst said walking robots will one day be a common sight – much like the automobile, and with a similar impact. The limiting factor has been the science and understanding of legged locomotion, but research at Oregon State has enabled multiple breakthroughs.

ATRIAS, developed in the Dynamic Robotics Laboratory, was the first robot to reproduce human walking gait dynamics. Following ATRIAS was Cassie, then came Agility’s humanoid robot Digit.

“In the not very distant future, everyone will see and interact with robots in many places in their everyday lives, robots that work alongside us and improve our quality of life,” Hurst said.

During the 5K, Cassie’s total time of 53 minutes included about 6.5 minutes of resets following two falls: one because of an overheated computer, the other because the robot was asked to execute a turn at too high a speed.

In a related project, Cassie has become adept at walking up and down stairs.



tags:


Oregon State University




            AIhub is supported by:



Related posts :

Learning to see the physical world: an interview with Jiajun Wu

and   17 Feb 2026
Winner of the 2019 AAAI / ACM SIGAI dissertation award tells us about his current research.

3 Questions: Using AI to help Olympic skaters land a quint

  16 Feb 2026
Researchers are applying AI technologies to help figure skaters improve. They also have thoughts on whether five-rotation jumps are humanly possible.

AAAI presidential panel – AI and sustainability

  13 Feb 2026
Watch the next discussion based on sustainability, one of the topics covered in the AAAI Future of AI Research report.

How can robots acquire skills through interactions with the physical world? An interview with Jiaheng Hu

  12 Feb 2026
Find out more about work published at the Conference on Robot Learning (CoRL).

From Visual Question Answering to multimodal learning: an interview with Aishwarya Agrawal

and   11 Feb 2026
We hear from Aishwarya about research that received a 2019 AAAI / ACM SIGAI Doctoral Dissertation Award honourable mention.

Governing the rise of interactive AI will require behavioral insights

  10 Feb 2026
Yulu Pi writes about her work that was presented at the conference on AI, ethics and society (AIES 2025).

AI is coming to Olympic judging: what makes it a game changer?

  09 Feb 2026
Research suggests that trust, legitimacy, and cultural values may matter just as much as technical accuracy.

Sven Koenig wins the 2026 ACM/SIGAI Autonomous Agents Research Award

  06 Feb 2026
Sven honoured for his work on AI planning and search.


AIhub is supported by:







 













©2026.01 - Association for the Understanding of Artificial Intelligence