Autonomous Interpretation of Demonstrations for Modification of Dynamical Movement Primitives
This addresses the need for more intuitive robot programming in motion modification, but it is incremental as it builds on existing DMP concepts.
The paper tackles the problem of adjusting dynamical movement primitives (DMPs) for robot motion by allowing operators to intuitively correct faulty trajectories through lead-through programming, resulting in a modified DMP that combines parts of the original and corrective trajectories, as verified experimentally.
The concept of dynamical movement primitives (DMPs) has become popular for modeling of motion, commonly applied to robots. This paper presents a framework that allows a robot operator to adjust DMPs in an intuitive way. Given a generated trajectory with a faulty last part, the operator can use lead-through programming to demonstrate a corrective trajectory. A modified DMP is formed, based on the first part of the faulty trajectory and the last part of the corrective one. A real-time application is presented and verified experimentally.