An Interaction Strategy for Safe Human Co-Working with Industrial Collaborative Robots

The assisted assembly of customized products supported by collaborative robots combined with mixed reality devices is the current trend in the Industry 4.0 concept. This article introduces an experimental work cell with the implementation of the assisted assembly process for customized cam switches as a case study. The research is aimed to design a methodology for this complex task with full digitalization and transformation data to digital twin models from all vision systems. Recognition of position and orientation of assembled parts during manual assembly are marked and checked by convolutional neural network (CNN) model. Training of CNN was based on a new approach using virtual training samples with single shot detection and instance segmentation. The trained CNN model was transferred to an embedded artificial processing unit with a high-resolution camera sensor. The embedded device redistributes data with parts detected position and orientation into mixed reality devices and collaborative robot. This approach to assisted assembly using mixed reality, collaborative robot, vision systems, and CNN models can significantly decrease assembly and training time in real production.

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"Programming - It’s not for Normal People": A Qualitative Study on User-Empowering Interfaces for Programming Collaborative Robots

10.1109/ro-man50785.2021.9515535 ◽

2021 ◽

Author(s):

Georgia Giannopoulou ◽

Elsi-Mari Borrelli ◽

Fiona McMaster

Keyword(s):

Qualitative Study ◽

Collaborative Robots ◽

Normal People

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Swarm Robotic Interactions in an Open and Cluttered Environment: A Survey

Designs ◽

10.3390/designs5020037 ◽

2021 ◽

Vol 5 (2) ◽

pp. 37

Author(s):

Maxime Vaidis ◽

Martin J.-D. Otis

Keyword(s):

Literature Review ◽

Research Trends ◽

Cluttered Environment ◽

Advantages And Disadvantages ◽

Population Migrations ◽

New Research ◽

Interaction Strategy ◽

Crowded Environment

Recent population migrations have led to numerous accidents and deaths. Little research has been done to help migrants in their journey. For this reason, a literature review of the latest research conducted in previous years is required to identify new research trends in human-swarm interaction. This article presents a review of techniques that can be used in a robots swarm to find, locate, protect and help migrants in hazardous environment such as militarized zone. The paper presents a swarm interaction taxonomy including a detailed study on the control of swarm with and without interaction. As the interaction mainly occurs in cluttered or crowded environment (with obstacles) the paper discussed the algorithms related to navigation that can be included with an interaction strategy. It focused on comparing algorithms and their advantages and disadvantages.

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Behavioural Study of the Force Control Loop Used in a Collaborative Robot for Sanding Materials

Materials ◽

10.3390/ma14010067 ◽

2020 ◽

Vol 14 (1) ◽

pp. 67

Author(s):

Rodrigo Pérez Ubeda ◽

Santiago C. Gutiérrez Rubert ◽

Ranko Zotovic Stanisic ◽

Ángel Perles Ivars

Keyword(s):

Force Control ◽

Feed Rate ◽

Significant Variation ◽

Industrial Robots ◽

Control Loop ◽

Saturation State ◽

Collaborative Robots ◽

Increase Productivity ◽

Different Characteristics ◽

Collaborative Robot

The rise of collaborative robots urges the consideration of them for different industrial tasks such as sanding. In this context, the purpose of this article is to demonstrate the feasibility of using collaborative robots in processing operations, such as orbital sanding. For the demonstration, the tools and working conditions have been adjusted to the capacity of the robot. Materials with different characteristics have been selected, such as aluminium, steel, brass, wood, and plastic. An inner/outer control loop strategy has been used, complementing the robot’s motion control with an outer force control loop. After carrying out an explanatory design of experiments, it was observed that it is possible to perform the operation in all materials, without destabilising the control, with a mean force error of 0.32%. Compared with industrial robots, collaborative ones can perform the same sanding task with similar results. An important outcome is that unlike what might be thought, an increase in the applied force does not guarantee a better finish. In fact, an increase in the feed rate does not produce significant variation in the finish—less than 0.02 µm; therefore, the process is in a “saturation state” and it is possible to increase the feed rate to increase productivity.

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