From the rhinoceros in Black Panther to Gollum in Lord of the Rings, humans have always had a fascinating with computer simulated animals. The results are usually varied – but we still haven’t got to a point where they look exactly lifelike.
That might be about to change.
Researchers at the University of Manchester have developed and fine-tuned a machine learning algorithm that improves the computer simulations of animals.
A report on phys.org revealed that the animal being used behind the machine learning model was a chimpanzee. This will not only help researchers improve their understanding of how the locomotion of animals functions, but also improve the technology behind it.
The idea behind the algorithm was to calculate the energy it takes to walk in a stable fashion, as compared to other movement patterns. A full-body scan of the chimpanzee was taken to create the model. Using this scan, the researchers generated an outline of the skeleton and the skin.
The skeletal model was then used to define the joints, muscles and limbs for the simulation. The final step involved analyzing the movement of the animal while it was made to walk.
Check out the video of the simulated chimpanzee walking below:
This study will be of great help to the animal bio-mechanical research community. Until now, machine learning algorithms were on the basic scale when it came to replicating the movement of animals. This should help speed along the process for everyone.
But outside that field, can you imagine how much more realistic those simulated animals will become in movies? From animated features to novel adaptations, this could be a potential game changer once it arrives in mainstream cinema.
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