Abstract
The development of Human Robot Collaborative (HRC) systems faces many challenges. First, HRC systems should be adaptable and re-configurable to support fast production changes. However, in the development of HRC applications safety considerations are of paramount importance, as much as classical activities such as task programming and deployment. Hence, the reconfiguration and reprogramming of executing tasks might be necessary also to fulfill the desired safety requirements. Model-based software engineering is a suitable means for agile task programming and reconfiguration. We propose a model-based design-to-deployment toolchain that simplifies the routine of updating or modifying tasks. This toolchain relies on (i) UML profiles for quick model design, (ii) formal verification for exhaustive search for unsafe situations (caused by intended or unintended human behavior) within the model, and (iii) trans-coding tools for automating the development process. The toolchain has been evaluated on a few realistic case studies. In this paper, we show a couple of them to illustrate the applicability of the approach.
Highlights
Collaborative robotic applications often need to be adaptable and reconfigurable to change behavior with respect to programmed tasks, to update devices or layout, etc
It presents the novel high-level modeling notation, based on the UML standard [32], that is at the core of the DESIGN module, and that allows users to describe the different aspects of an Human Robot Collaborative (HRC) application: the task to be collaboratively performed by human operators and robots and the workspace in which they operate
In this paper we have introduced a tool-supported modeldriven approach to (i) create models of HRC applications, (ii) automatically perform formal verification on them, and (iii) deploy corresponding function blocks
Summary
Collaborative robotic applications often need to be adaptable and reconfigurable to change behavior with respect to programmed tasks, to update devices or layout, etc. Operators in Flexible Manufacturing Systems (FMS) are no longer bound to a single station with fixed action schedules;instead, they can devote more added-value time to supervising tasks, as in the collaborative robotic application used to validate. These authors contributed to the work presented in this article: Mehrnoosh Askarpour, Livia Lestingi, Samuele Longoni. Examples of physically- or mentally-heavy workload tasks that benefit from collaborative robots include, but are not limited to: setting fixtures, mounting/dismounting workpieces into fixtures before/after machining, inspecting the pre-machining setups, inspecting the quality of machined parts In these cases, robots can provide a number of assistive tasks such as kitting parts and tools, handling parts, supporting manual assembly, moving sensors for inspections, etc., according to nominal task plans or inline alternatives requested by operators. The actual creation of collaborative tasks can be done by different actors in several ways: through automatic composition of programs by factory planners/schedulers [25, 53], if robot-level control is part of their architecture [30] and whenever human tasks can be modeled [9]; through off-line programming
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