New technology helps humanoid robots improve 'self-recovery' after falling
Humanup’s randomization improved robustness on varied terrains, achieving 78.3% get-up and 98.3% roll-over success rates. Researchers introduce a breakthrough in robot autonomy A team at the University of Illinois Urbana-Champaign has developed a machine-learning framework that allows humanoid robots to autonomously get up after falling . This is the first successful demonstration of learned fall-recovery strategies for human-sized humanoid robots in real-world conditions. Named HUMANUP , the framework is designed to enhance robot autonomy, making them more adaptable for various applications. “Hand-designing controllers for getting up is difficult because of the varied configurations a humanoid can end up in after a fall and the challenging terrains humanoid robots are expected to operate on,” said researchers in the study paper. “This paper develops a learning framework to produce controllers that enable humanoid robots to get up from varying configurations on varying terrains.”...