Error-tolerant execution of complex robot tasks based on skill primitives

This paper presents a general approach to specify and execute complex robot tasks considering uncertain environments. Robot tasks are defined by a precise definition of so-called skill primitive nets, which are based on Mason's hybrid force/velocity and position control concept, but it is not limited to force/velocity and position control. Two examples are given to illustrate the formally defined skill primitive nets. We evaluated the controller and the trajectory planner by several experiments. Skill primitives suite very well as interface to robot control systems. The presented hybrid control approach provides a modular, flexible, and robust system; stability is guaranteed, particularly at transitions of two skill primitives. With the interface explained here, the results of compliance motion planning become possible to be examined in real work cells. We have implemented an algorithm to search for mating directions in up to three-dimensional configuration-spaces. Thereby, on one hand we have released compliant motion control concepts and on the other hand we can provide solutions for fine motion and assembly planning. This paper shows, how these two fields can be combined by the general concept of skill primitive nets introduced here, in order to establish a powerful system, which is able to automatically execute prior calculated assembly plans based on CAD-data in uncertain environments.