Preparation and control of intelligent automation systems
Doctoral thesis, 2021
In the automation systems of tomorrow, it is likely that the devices included have various degrees of autonomy, and include advanced algorithms for perception and control. Human operators will be expected to work together with collaborative robots as well as with roaming robots for material handling.
The volatile nature of the environment of such intelligent automation systems lead to an enormous amount of possible situations that can arise and which need to be suitably handled. This complexity makes development of control systems for intelligent automation systems difficult using traditional methods.
As an alternative, this thesis presents a model-based control framework, which uses a combination of formal specification and automated planning. The proposed framework allows for defining the intentions of the automation system on a high level, which enables decisions that influence when things should occur to be modeled using logical constraints, rather than programming. To achieve a modular framework, low level, reusable, resource models are composed by 1) formal specification to ensure safety and 2) applying an abstraction called an operation, which couples the reusable resources to the intentions of the system. By planning also the resources' detailed actions, the operations can, when possible, be completed regardless of the resources' current state. This eases error-recovery, as resources do not have to be reset when an error occurs.
Additionally, the thesis proposes an iterative and interactive workflow for integrating the proposed model-based control framework into a virtual preparation process, using computer-based simulation as a tool for validating formal specifications. The control framework allows for adding new constraints to a running system, enabling an efficient and interactive preparation process.
The framework has been applied to a use case from final assembly, which features human-robot collaboration. Experimental results on the ability to handle unforeseen errors and planning performance are presented.
The volatile nature of the environment of such intelligent automation systems lead to an enormous amount of possible situations that can arise and which need to be suitably handled. This complexity makes development of control systems for intelligent automation systems difficult using traditional methods.
As an alternative, this thesis presents a model-based control framework, which uses a combination of formal specification and automated planning. The proposed framework allows for defining the intentions of the automation system on a high level, which enables decisions that influence when things should occur to be modeled using logical constraints, rather than programming. To achieve a modular framework, low level, reusable, resource models are composed by 1) formal specification to ensure safety and 2) applying an abstraction called an operation, which couples the reusable resources to the intentions of the system. By planning also the resources' detailed actions, the operations can, when possible, be completed regardless of the resources' current state. This eases error-recovery, as resources do not have to be reset when an error occurs.
Additionally, the thesis proposes an iterative and interactive workflow for integrating the proposed model-based control framework into a virtual preparation process, using computer-based simulation as a tool for validating formal specifications. The control framework allows for adding new constraints to a running system, enabling an efficient and interactive preparation process.
The framework has been applied to a use case from final assembly, which features human-robot collaboration. Experimental results on the ability to handle unforeseen errors and planning performance are presented.
Online,
Opponent: Professor Valeriy Vyatkin, Information Technology in Automation, Aalto University
Author
Martin Dahl
Chalmers, Electrical Engineering, Systems and control
Integrated Virtual Preparation and Commissioning: supporting formal methods during automation systems development
IFAC-PapersOnLine,;Vol. 49(2016)p. 1939-1944
Paper in proceeding
Guard extraction for modeling and control of a collaborative assembly station
IFAC-PapersOnLine,;Vol. 53(2020)p. 223-228
Paper in proceeding
Sequence Planner: A Framework for Control of Intelligent Automation Systems
Applied Sciences (Switzerland),;Vol. 12(2022)
Journal article
Interactive formal specification for efficient preparation of intelligent automation systems
CIRP Journal of Manufacturing Science and Technology,;Vol. 38(2022)p. 129-138
Journal article
Application of the sequence planner control framework to an intelligent automation system with a focus on error handling
Machines,;Vol. 9(2021)
Journal article
This thesis highlights our work on preparation and control of automation systems. The focus has been mainly on production systems, moving from very high levels of automation in welding car bodies (body in white) where everything is static, predefined, and in a cage, to systems which involve more autonomous components such as roaming robots and systems which involve human-robot collaboration.
Starting with case studies from body in white, we developed a framework for integrating formal methods in the development of control systems early in the process, using computer based simulation as a tool for validating formal specifications. We identified that use of formal methods in the field of automation systems is lacking and a hypothesis arose that an approach that is more integrated in the familiar engineering workflow could be beneficial for adoption.
When moving on to automation systems that include autonomous components and human operators, and which rely on advanced algorithms for perception, we have found that traditional methods for control system development are hard to scale. The volatile nature of the environment of such systems lead to an enormous amount of possible situations that can arise and need to be suitably handled. To tackle this increase in complexity we have developed a control system based on formal models, which drives the system towards its goal using automated planning.
This goal-oriented control system ties well with the integrated virtual engineering workflow; the simulation can help to answer the question “why did it do that” when there are multiple subsystems that takes decisions. The design of the control system allows the automation system to be constrained in order to avoid undesired outcomes while it's live in the simulated world.
Human-robot collaboration implies a natural trade-off between efficiency and safety. While collaborative robots are supposedly “safe” to be near, this is only true at low speed and with light tools that do not pose a danger to the operator. These concerns makes the human-robot collaboration inherently a slow system. But, by deciding on a plan together with the control system, it may be possible to speed up execution to increase efficiency. This joint deliberation between the human operator and the automation system becomes possible in the proposed control framework, paving the way for future research in this direction.
Starting with case studies from body in white, we developed a framework for integrating formal methods in the development of control systems early in the process, using computer based simulation as a tool for validating formal specifications. We identified that use of formal methods in the field of automation systems is lacking and a hypothesis arose that an approach that is more integrated in the familiar engineering workflow could be beneficial for adoption.
When moving on to automation systems that include autonomous components and human operators, and which rely on advanced algorithms for perception, we have found that traditional methods for control system development are hard to scale. The volatile nature of the environment of such systems lead to an enormous amount of possible situations that can arise and need to be suitably handled. To tackle this increase in complexity we have developed a control system based on formal models, which drives the system towards its goal using automated planning.
This goal-oriented control system ties well with the integrated virtual engineering workflow; the simulation can help to answer the question “why did it do that” when there are multiple subsystems that takes decisions. The design of the control system allows the automation system to be constrained in order to avoid undesired outcomes while it's live in the simulated world.
Human-robot collaboration implies a natural trade-off between efficiency and safety. While collaborative robots are supposedly “safe” to be near, this is only true at low speed and with light tools that do not pose a danger to the operator. These concerns makes the human-robot collaboration inherently a slow system. But, by deciding on a plan together with the control system, it may be possible to speed up execution to increase efficiency. This joint deliberation between the human operator and the automation system becomes possible in the proposed control framework, paving the way for future research in this direction.
Virtual Commissioning of Vehicle Maintenance Operations, UNIFICATION
VINNOVA (2017-02245), 2017-06-01 -- 2020-05-31.
Virtual Commissioning of Production Systems - including PLC logics
VINNOVA (2014-01408), 2014-07-01 -- 2017-06-30.
Areas of Advance
Information and Communication Technology
Production
Subject Categories
Robotics
ISBN
978-91-7905-446-5
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4913
Publisher
Chalmers
Online,
Opponent: Professor Valeriy Vyatkin, Information Technology in Automation, Aalto University