One of the first things you discover in the world of robotics is the complexity of simple tasks. Things that appear simple to humans have potentially infinite variables that we take for granted. Robots don’t have such luxuries.
That’s precisely why much of the industry is focused on repeatable tasks in structured environments. Thankfully, the world of robotic learning has seen some game-changing breakthroughs in recent years, and the industry is on track for the creation and deployment of more adaptable systems.
Last year, Google DeepMind’s robotics team showcased Robotics Transformer — RT-1 — which trained its Everyday Robot systems to perform tasks like picking and placing and opening draws. The system was based on a database of 130,000 demonstrations, which resulted in a 97% success rate for “over 700” tasks, according to the team.
