Event-driven industrial robot control architecture for the Adept V+ platform
Artikel i vetenskaplig tidskrift, 2019

Modern industrial robotic systems are highly interconnected. They operate in a distributed environment and communicate with sensors, computer vision systems, mechatronic devices, and computational components. On the fundamental level, communication and coordination between all parties in such distributed system are characterized by discrete event behavior. The latter is largely attributed to the specifics of communication over the network, which, in terms, facilitates asynchronous programming and explicit event handling. In addition, on the conceptual level, events are an important building block for realizing reactivity and coordination. Eventdriven architecture has manifested its effectiveness for building loosely-coupled systems based on publish-subscribe middleware, either general-purpose or robotic-oriented. Despite all the advances in middleware, industrial robots remain difficult to program in context of distributed systems, to a large extent due to the limitation of the native robot platforms. This paper proposes an architecture for flexible event-based control of industrial robots based on the Adept V+ platform. The architecture is based on the robot controller providing a TCP/IP server and a collection of robot skills, and a high-level control module deployed to a dedicated computing device. The control module possesses bidirectional communication with the robot controller and publish/subscribe messaging with external systems. It is programmed in asynchronous style using pyadept, a Python library based on Python coroutines, AsyncIO event loop and ZeroMQ middleware. The proposed solution facilitates integration of Adept robots into distributed environments and building more flexible robotic solutions with eventbased logic.

Coroutines

Adept

System composability

Computer vision

Robot architecture

Concurrency

ZeroMQ

AsyncIO

Communication protocols

Robotics

Författare

Oleksandr Semeniuta

Norges teknisk-naturvitenskapelige universitet

Petter Falkman

Chalmers, Elektroteknik, System- och reglerteknik

PeerJ Computer Science

23765992 (eISSN)

7 e207

Ämneskategorier

Inbäddad systemteknik

Robotteknik och automation

Datavetenskap (datalogi)

DOI

10.7717/peerj-cs.207

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2023-03-21