Plethora : a framework for the intelligent control of robotic assembly systems

The thesis describes a distributed software environment designed for the development, evaluation and comparison of new techniques in knowledge based control of robot assembly work cells. It has characteristics which fulfil deficiencies within previous systems and contains within it new techniques in task specification, distributed control[1,2], object recognition[3,4] and path planning[5]. The control of the resources within the cell is based upon an extension of the facilities of a classical blackboard architecture to include plan execution. Unlike previous schemes, these additions allow Plethora to reason about the intent of an action, the current state of the cell and asynchronous events within a single framework. It is this seamless operation and extended representational adequacy that allows Plethora to explore new techniques dealing with the uncertainty inherent in a flexible work cell. The task is specified in domain terms and interpreted to produce a partially ordered set of goals. This new technique is based upon a two-stage ordering process using constructional constraints and necessary collision avoidance. Two new methods, one for object identification and the other for path planning, have also been developed using the system. These have two advantages, efficiency and the ability to operate on data from a vision system or Plethora's geometric modeller. Both methods can be completed within the critical times typical of an assembly work cell. Finally, results of an experiment using the system on a laboratory work cell illustrate how it encompasses previous techniques and can be used to develop new techniques not possible with earlier architectures.