In recent years, developers have created a wide range of sophisticated robots that can operate in specific environments in increasingly efficient ways. The body structure of many among these systems is inspired by nature, animals, and humans.
Although many existing robots have bodies that resemble those of humans or other animal species, programming them so that they also move like the animal they are inspired by is not always an easy task. Doing this typically entails the development of advanced locomotion controllers, which can require considerable resources and development efforts.
Researchers at DeepMind have recently created a new technique that can be used to efficiently train robots to replicate the movements of humans or animals. This new tool, introduced in a paper pre-published on arXiv, is inspired from previous work that leveraged data representing real-world human and animal movements, collected using motion capture technology.
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