Teaching robots to tackle new tasks can be both time-consuming and costly. Moreover, additional training sometimes hinders their performance on previously learned tasks.

Researchers at Beijing Institute of Technology, X SQUARE ROBOT and Tsinghua University recently developed HOST (Human-to-robot One-Shot Skill AcquisiTion), a new framework that could allow robots to acquire new skills faster and more efficiently. Their proposed learning approach, introduced in a paper posted to the arXiv preprint server, allows a robot to acquire a new skill from a single video showing a human demonstration without compromising previously acquired abilities.

“The ability to acquire skills rapidly and effortlessly while retaining those already mastered is essential for robots,” wrote Guangyan Chen, Meiling Wang and their colleagues in their paper.