The research, recently published by the Royal Society Open Science Journal, shows how simple changes to ‘machine learning’ algorithms can produce better looking, more accurate computer-generated animal simulations. It will also help researchers investigate the ‘curious way’ that all primates walk and how this might be linked to stability whilst moving through the trees.
Professor Bill Sellers says: “Starting from an animal’s skeleton, computers using machine learning can now reconstruct how the animal could have moved. However, they don’t always do a good job”.
“But with some simple changes to the machine learning goals we can now create much more accurate simulations. We’ve now used this process to generate chimpanzee locomotion to explore why they walk the way they do”.
A full body CT scan of an adult male common chimpanzee was used to create a chimpanzee model. This scan was then used to generate a skeletal model and a skin outline which was then used to define joint positions, muscle paths and limb contact points for the simulation.
Prof Sellers explains: “As technology has advanced and with musculoskeletal models becoming increasingly sophisticated, previous simulation models are becoming extremely unrealistic in relation to gait patterns so we have to adapt the way we think and research.”