Robotics engineers have worked for decades and invested many millions of research dollars in attempts to create a robot that can walk or run as well as an animal. And yet, it remains the case that many animals are capable of feats that would be impossible for robots that exist today.
A research team has shown for the first time that reinforcement learning—i.e., a neural network that learns the best action to perform at each moment based on a series of rewards—allows autonomous vehicles and underwater robots to locate and carefully track marine objects and animals.
A team has shown that reinforcement learning -i.e., a neural network that learns the best action to perform at each moment based on a series of rewards- allows autonomous vehicles and underwater robots to locate and carefully track marine objects and animals.
Four-legged animals are innately capable of agile and adaptable movements, which allow them to move on a wide range of terrains. Over the past decades, roboticists worldwide have been trying to effectively reproduce these movements in quadrupedal (i.e., four-legged) robots.