Dynamic model can generate realistic human motions and edit existing ones
When exploring their surroundings, communicating with others and expressing themselves, humans can perform a wide range of body motions. The ability to realistically replicate these motions, applying them to human and humanoid characters, could be highly valuable for the development of video games and the creation of animations, content that can be viewed using virtual reality (VR) headsets and training videos for professionals.
Humans can innately perform a wide range of movements, as this allows them to best tackle various tasks in their day-to-day life. Automatically reproducing these motions in virtual avatars and 3D animated human-like characters could be highly advantageous for many applications, ranging from metaverse spaces to digital entertainment, AI interfaces…
Performing human-like motions that involve multiple contacts is challenging for robots. In this regard, a researcher 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…
An international group of researchers has created a new approach to imitating human motion by combining central pattern generators (CPGs) and deep reinforcement learning (DRL). The method not only imitates walking and running motions but also generates movements for frequencies where motion data is absent, enables smooth transition movements from…