


CMUÐ achieves a breakthrough: the robot dog has a full agility value, can cross obstacles at super high speed, and has both speed and safety!
CMU and ETH Zurich teams collaborated to develop a new framework called "Agile But Safe" (ABS), which provides a solution for quadruped robots to achieve high-speed movement in complex environments. The framework not only shows high efficiency in avoiding collisions, but also achieves an unprecedented 3.1 millisecond speed. This innovation brings new progress to the field of legged robots.
In the field of high-speed robot motion, maintaining speed and safety at the same time has always been a huge challenge. However, a research team at Carnegie Mellon University (CMU) and ETH Zurich (ETH) recently achieved a breakthrough. The new quadruped robot algorithm they developed can not only move quickly in complex environments, but also skillfully avoid obstacles, truly achieving the goal of "agility and safety". The innovation of this algorithm lies in its ability to quickly identify and analyze the surrounding environment and make intelligent decisions based on real-time data. By using advanced sensors and powerful computing power, the robot is able to accurately sense obstacles around it and avoid them by adjusting its gait and trajectory. The successful application of this technology will greatly promote the development of high-speed robots
Paper address: https://arxiv.org/pdf/2401.17583.pdf
With the support of ABS, the robot dog has demonstrated amazing high-speed obstacle avoidance capabilities in various scenarios:
Narrow corridors with many obstacles:
Messy indoor scenes:
Whether it is grass or outdoors, static or dynamic obstacles, the robot dog can handle them calmly:
When encountering a stroller, the robot dog dodges nimbly:
Warning signs, boxes, and chairs are also not a problem:
It can also easily bypass the sudden appearance of mats and human feet:
The robot dog can even play eagle and catch chickens:
ABS Breakthrough Technology:
RL Learning model-free Reach-Avoid value
ABS adopts a dual policy (Dual Policy) setting, including an "Agile Policy" (Agile Policy) and a "Recovery Policy" (Recovery Policy). Agility strategies allow the robot to move quickly through obstacles, while recovery strategies step in to ensure the safety of the robot once Reach-Avoid Value Estimation detects potential dangers (such as a sudden appearance of a stroller).



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