Performing human-like motions that involve multiple contacts is challenging for robots. In this regard, a researcher from the Tokyo University Science has envisioned an interactive cyber-physical human (iCPH) platform with complementary humanoid (physical twin) and simulation (digital twin) elements.
iCPH combines human measurement data, musculoskeletal analysis, and machine learning for data collection and augmentation. As a result, iCPH can understand, predict, and synthesize whole-body contact motions.
Humans naturally perform numerous complex tasks. These include sitting down, picking something up from a table, and pushing a cart. These activities involve various movements and require multiple contacts, which makes it difficult to program robots to perform them. [Read more…] about Interactive cyber-physical human: Generating contact-rich whole-body motions