Robots with different bodies can now share skills: What intention-based learning changes
Robots are increasingly being used in manufacturing, agriculture and health care. But programming a team of robots to carry out individual tasks raises a question: How can robots learn from other robots if they are built differently? A multi-institutional team including Chongjie Zhang, an associate professor of computer science and engineering at WashU McKelvey Engineering, have developed a new method that enables robots to achieve intentions shown by their peers.
From wiping up spills to serving up food, robots are being taught to carry out increasingly complicated household tasks. Many such home-bot trainees are learning through imitation; they are programmed to copy the motions that a human physically guides them through.
Imagine a team of humans and robots working together to process online orders -- real-life workers strategically positioned among their automated coworkers who are moving intelligently back and forth in a warehouse space, picking items for shipping to the customer. This could become a reality sooner than later, thanks to…