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Augmenting Human Operators for the Era of Automated Industry - A/HOPE/AI

Reference number
Coordinator KUNGLIGA TEKNISKA HÖGSKOLAN - School of Electrical Engineering and Computer Science
Funding from Vinnova SEK 490 000
Project duration November 2018 - August 2019
Status Completed
Venture The strategic innovation programme for Production2030
Call Idea projects for new services for manufacturing industry

Purpose and goal

The project established a consortium exploring innovative solutions to support human operators in performing industrial tasks, considering low latency 5G networks and upcoming Industry 4.0 applications. Based on input from project partners and their immediate industrial ecosystem, a number of relevant applications of AR/MR have been identified and developed in an experimental testbed. These have been tested with real users to quantify the impact of the proposed solutions on both the quality of work life and efficiency in accomplishing critical tasks.

Expected results and effects

- Examples of novel digital-to-physical interaction modalities that are specific for human-centric industrial applications. - A set of demonstrators showcasing (a) Human-to-Human (b) Human-to-Machine and (c) Human-to-AI solutions for Industry 4.0 tasks. - Initial experimental results and data from user testing. - The establishment of an advanced “sandbox” for building and testing novel VR / AR based industry 4.0 services.

Planned approach and implementation

A core component of the project activities consisted of workshops designed to identify key areas of applications that are unfulfilled by existing technologies. Based on that, an initial set of demonstrators have been developed and used in workshops with external industrial partners to 1) refine the concepts based on their expertise and experienced pain points, 2) to engage them in project ecosystem for designing a joint follow-up research project. The refined demonstrators have then been used with real users to quantify KPIs aiming at both QoE assessment and production efficiency.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 30 October 2018

Reference number 2018-03980

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