Abstract
Abstract This paper considers programming and control of skill-based robots. Robot skills are used to integrate and synchronize robot actions and sensor data in a consistent way. Skill-based approach provides a framework for configurable robot systems, enabling quick setups and start-ups of applications. In the paper we will introduce skill programming and skill control concepts in more detail and how they relate to usage of models and sensors. We will also give a practical example for programming and implementing skills for a grinding application.
Highlights
With ever-increasing demands for agility and flexibility, robotized manufacturing is facing challenges and barriers to the use of robots because; the high cost of engineering the work cells
This paper considers programming and control of skill-based robots
In the paper we will introduce skill programming and skill control concepts in more detail and how they relate to usage of models and sensors
Summary
With ever-increasing demands for agility and flexibility, robotized manufacturing is facing challenges and barriers to the use of robots because; the high cost of engineering the work cells (i.e., the design, fabrication, and installation of jigs, fixtures, conveyors, and third-party sensors and software). Schou et al [8] presents a similar hierarchical functional modelling and parametrization approach to task-level programming In their system, only some parameters were specified off-line (e.g. velocity, object type etc.) and all the locations were taught on-line. Skills are specified with (configuration) parameters, and our integrated tool supports setting and computing these, using a robot off-line programming tool with our extensions. Skill models are designed and programmed by expert users but they could be re-configured for different situations even by operators who have no experience in robot programming This is achieved by making skills intuitive object-centered robot abilities, where they are applied on physical entities instead of 3D coordinates [5]. In which pc is the corresponding center point in the object’s CAD coordinate system and pc is the cluster center point in the sensor’s coordinate system
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