Robotic

Control system

Robotic control systems integrate multiple sensors and effectors, have many interacting degrees of freedom and require operator interfaces, programming tools and real-time capabilities. They are often connected to wider communication networks, including the Internet of things, a network correlating physical objects. Progress towards open architecture, layered, user-friendly and 'intelligent' sensor-based interconnected robots has emerged from earlier concepts related to flexible manufacturing systems. Further, several 'open or 'hybrid' reference architectures provide advantages over prior 'closed' robot control systems. Open-architecture controllers are said to be better able to meet the growing requirements of a wide range of robot users, including system developers, end users and research scientists, and are better positioned to contribute advanced industrial concepts. In addition to utilizing many established features of robot controllers, such as position, velocity and force control of end effectors, they also enable interconnection and the implementation of more advanced sensor fusion and control techniques, including adaptive control, fuzzy control and artificial neural network–based control. When implemented in real time, such techniques can potentially enable more adaptive control systems when working in unfamiliar environments. Generic reference architecture and associated interconnected, open-architecture robot and controller implementation has been used in a number of studies.