Control components for Collaborative and Intelligent Automation Systems

Dahl, Martin; Erős, Endre; Hanna, Atieh; Bengtsson, Kristofer; Fabian, Martin; Falkman, Petter

doi:10.1109/etfa.2019.8869112

Cited by 8 publications

(6 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed framework handles the increase in complexity brought by intelligent automation by off-loading difficult modeling tasks to control logic synthesis algorithms and the specifics of execution to an online planning system. This paper builds on the previous publications [10,20,22] and introduces new abstractions: operations and intentions, which enable hierarchical modeling and planning to make it easier to handle larger systems than in previous work.…”

Section: Contributionmentioning

confidence: 99%

“…This paper presents a control framework for ROS that aims to aid in controlling multiple interdependent resources. The resources are modeled independently as components that include formal models of their behavior [20,21] and are controlled using a low-level planner. In order to ensure safe execution, constraints derived from safety specifications are added to restrict the planning system [22].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Sequence Planner: A Framework for Control of Intelligent Automation Systems

et al. 2022

Self Cite

View full text Add to dashboard Cite

This paper presents a framework that tackles the challenges met in the development of automation systems featuring collaborative robotics and other machines that have some degree of autonomy. These machines rely on online algorithms for both sensing and acting in order to achieve a very high level of flexibility. To take advantage of these new machines and algorithms, control systems must also be increasingly flexible. In this paper, we present a framework for control of this new class of intelligent automation systems called Sequence Planner (SP), which helps with control of both traditional automation equipment and machines with autonomy. To aid the complex task of developing automation control solutions, SP relies on supporting algorithms for control logic synthesis and online planning. SP has been implemented with plug-in support for the Robot Operating System (ROS) and applied to an industrial demonstrator. We present our findings on how SP performed as a control system for this demonstrator, where we show that it is an adequate approach to implement automation for a highly flexible single station system. As a standardized way of automating such systems is missing, we hope that our contribution will provide a foundation for how to develop intelligent automation systems.

show abstract

Section: Contributionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sequence Planner: A Framework for Control of Intelligent Automation Systems

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…A prerequisite for such a workplace is that an intuitive and bidirectional interface should be in place to enable efficient handshaking and checking, to indicate continuously the transition between the different collaborative tasks and to avoid erroneous action by either party. In case of changes to the plan, the operator and the robot system have to consult and deliberate with each other, via the intelligent human-in-theloop control system [20], before changing the agreed plan. If the robot system anyway makes an undesired motion or action, the adaptive safety function should be active when executing plans with an increased risk.…”

Section: Fig 7 Deliberation In Planning and Acting Modementioning

confidence: 99%

Towards safe human robot collaboration - Risk assessment of intelligent automation

Hanna

Bengtsson

Götvall

et al. 2020

2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

Self Cite

View full text Add to dashboard Cite

Automation and robotics are two enablers for developing the Smart Factory of the Future, which is based on intelligent machines and collaboration between robots and humans. Especially in final assembly and its material handling, where traditional automation is challenging to use, collaborative robot (cobot) systems may increase the flexibility needed in future production systems. A major obstacle to deploy a truly collaborative application is to design and implement a safe and efficient interaction between humans and robot systems while maintaining industrial requirements such as cost and productivity. Advanced and intelligent control strategies is the enabler when creating this safe, yet efficient, system, but is often hard to design and build. This paper highlights and discusses the challenges in meeting safety requirements according to current safety standards, starting with the mandatory risk assessment and then applying risk reduction measures, when transforming a typical manual final assembly station into an intelligent collaborative station. An important conclusion is that current safety standards and requirements must be updated and improved and the current collaborative modes defined by the standards community should be extended with a new mode, which in this paper is refereed to the deliberative planning and acting mode.

show abstract

“…Over the years, other aspects have been integrated, like formal verification and synthesis using Supremica [16], restart support [17], cycle time optimization [18], energy optimization and hybrid systems [19], online monitoring and control [20], as well as emergency department online planning support [21]. Recently, effort has been spent to use the developed algorithms and visualization techniques for control and coordination of ROS-and ROS2-based systems [22]. This section will give an overview of how SP can be used to develop ROS2-based automation systems.…”

Section: A New Control Infrastructurementioning

confidence: 99%

Development of an Industry 4.0 Demonstrator Using Sequence Planner and ROS2

Erős

Dahl

Hanna

et al. 2020

Studies in Computational Intelligence

Self Cite

View full text Add to dashboard Cite

In many modern automation solutions, manual off-line programming is being replaced by online algorithms that dynamically perform tasks based on the state of the environment. Complexities of such systems are pushed even further with collaboration among robots and humans, where intelligent machines and learning algorithms are replacing more traditional automation solutions. This chapter describes the development of an industrial demonstrator using a control infrastructure called Sequence Planner (SP), and presents some lessons learned during development. SP is based on ROS2 and it is designed to aid in handling the increased complexity of these new systems using formal models and online planning algorithms to coordinate the actions of robots and other devices. During development, SP can auto generate ROS nodes and message types as well as support continuous validation and testing. SP is also designed with the aim to handle traditional challenges of automation software development such as safety, reliability and efficiency. In this chapter, it is argued that ROS2 together with SP could be an enabler of intelligent automation for the next industrial revolution.

show abstract

Control components for Collaborative and Intelligent Automation Systems

Cited by 8 publications

References 13 publications

Sequence Planner: A Framework for Control of Intelligent Automation Systems

Sequence Planner: A Framework for Control of Intelligent Automation Systems

Towards safe human robot collaboration - Risk assessment of intelligent automation

Development of an Industry 4.0 Demonstrator Using Sequence Planner and ROS2

Contact Info

Product

Resources

About