Learning from demonstration: repetitive movements for autonomous service robotics

This paper presents a method for learning and generating rhythmic movement patterns based on a simple central oscillator. It can be used to generate cyclic movements for a robot system which has to solve complex tasks. The system is laid out in such a way that multiple motion dimensions, or degrees of freedom of the robot, are represented independent of each other; therefore, an extension to higher-dimensional problems is easily possible. Guiding the robot by holding its end-effector, the user teaches simple movement primitives forming the basis for a more complex task. Each movement primitive is represented in the system using an oscillator combined with a learned nonlinear mapping. These primitives are then optimally combined to a complete solution to the posed problem. Said optimality is obtained using simulated annealing with the A* global search algorithm. Our approach is demonstrated on the problem of wiping a table, but can be used for many typical problems in service and household robotics.