Putting a set of sensors on an Eskimo dog all the time to collect data
To accomplish this, the researchers put a set of basic sensors on an Eskimo dog named Kelp M. Redmon. They put in Kelp's head. A GoPro camera.， 6 inertial measurement units (on the legs, tail and body, respectively) to determine the position of the object. A microphone. and one that ties that data together Arduino Development Boards。
They spent many hours recording the dog's activities - walking in different environments, fetching, playing at the dog park, eating - and synchronizing the dog's movements with the environment he saw. The result is the formation of a Dataset of Ego-Centric Actions in a Dog Environment with the dog itself as the perspective, referred to as DECADE dataset . Researchers used this dataset to train a new AI intelligences.
For this agent, some sort of sensory input is given - such as a view of a room or street, or a ball flying by - to predict what the dog will do in this situation. Of course, without going into particular detail, even just figuring out how its body moves and where it moves to is already a pretty important task.
Hessam Bagherinezhad of the University of Washington, one of the researchers, explained, "It learned how to move the joints in order to walk, learned how to walk or run again is to avoid obstacles. ""He learned to run after squirrels, follow his owner around, and chase flying dog toys (while playing Frisbee). These are some of the basic AI tasks in computer vision and robotics (e.g., motion planning, walkable surfaces, object detection, object tracking, person recognition) that we have been trying to solve by collecting separate data for each task.”