Abstract
Industrial robots in manufacturing systems offer high flexibility: In addition to their potential use in different processes such as handling and assembly, their tasks can be reconfigured in software after commissioning and even during operation. Manufacturing cells that primarily use robots or other programmable subsystems can therefore offer a high degree of flexibility, as different products can be processed in the same system as well as the system being simpler to scale up or down for changing demand. Conventional robot control (RC) systems, as found in commercial industrial robots, typically only control the tasks of single robots or a select few of robots and their accessories and tools. Offline planning and programming tools allow the different RC’s programming to be derived for a specific cell layout and overall task. This conventional approach has a number of limitations that negatively affect the system’s flexibility: the derived programming is only valid for a specific layout, also, assumptions have to be made regarding all possible collisions that arise from both static and moving objects in the cell at the time of planning, making the integration of autonomous vehicles and other systems (e.g., CNC machines) more difficult. This work proposes a control system that uses a holistic model of the manufacturing cell, comprised of all static and dynamic objects, for collision detection and path planning for directly controlling all actuators inside the cell in real-time. This system allows for interaction with non-directly controllable systems within the cell, e.g., AGVs. The requirements for this control system are derived from a reference: a robotic manufacturing cell comprised of multiple robots with overlapping kinematic work areas, multiple selected processes and their respective equipment as well as AGVs. The physical instance of this reference cell can also be used for validating and demonstrating of the controls system.
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