遊び好きな犬型ロボット：俊敏かつ精密な四足歩行の学習
Playful DoggyBot: Learning Agile and Precise Quadrupedal Locomotion
強化学習で知覚と制御を分離したシステムを構築し、四足ロボットが最大3m/sの飛来するボールを追跡したり、跳躍して空中の小さな物体を捕まえるなど、犬のような俊敏で精密な動作を実現した。
著者: Xin Duan, Ziwen Zhuang, Hang Zhao, Soeren Schwertfeger
分類: cs.RO
原文アブストラクト
Quadrupedal animals can perform agile and playful tasks while interacting with real-world objects. For instance, a trained dog can track and catch a flying frisbee before it touches the ground, while a cat left alone at home may leap to grasp the door handle. Successfully grasping an object during high-dynamic locomotion requires highly precise perception and control. However, due to hardware limitations, agility and precision are usually a trade-off in robotics problems. In this work, we employ a perception-control decoupled system based on Reinforcement Learning (RL), aiming to explore the level of precision a quadrupedal robot can achieve while interacting with objects during high-dynamic locomotion. Our experiments show that our quadrupedal robot, mounted with a passive gripper in front of the robot's chassis, can perform both tracking and catching tasks similar to a real trained dog. The robot can follow a mid-air ball moving at speeds of up to 3m/s and it can leap and successfully catch a small object hanging above it at a height of 1.05m in simulation and 0.8m in the real world.
