- Research Project
A future that works Cobotics, digital skills and the re-humanization of the workplace
In a longitudinal study, the effects of the introduction of cobots on the work culture, the demands on the work activity and the subjective work experience of the employees are investigated. Based on these findings and on user testing, a robotic solution is developed that aims at fostering empowering interactions while meeting industrial requirements such as productivity, quality and flexibility.
- Lead department Engineering and information technology
- Additional departments Business
Institute for Human Centered Engineering (HUCE)
Institute for New Work
- Research unit HUCE / HuCE – roboticsLab
- Duration (planned) 01.05.2020 - 30.04.2024
- Project management Sarah Degallier Rochat
- Head of project Sarah Degallier Rochat
Charly Blanc (TI)
Nada Endrissat (W)
New technologies such as collaborative robotics and artificial intelligence are transforming work. While economists often discuss questions of the effects on the quantity of work - i.e. the extent to which the automation of processes and the use of robots can destroy jobs or create new ones - this project, which is supported by the SNF, is devoted to questions of quality. The focus is on Collaborative Robots, or cobots for short. Cobots meet very specific safety requirements and can therefore be used in direct collaboration with humans, making them particularly suitable for processes that are difficult to fully automate and are still done manually such as: small production series, products with short life cycles, low-added value processes or processes that require a high dexterity or flexibility. The process can be partially automated: repetitive, typical, easy-to-automate tasks are overtaken by the robot while more difficult, specific tasks are still done manually. This leads to a distribution of the tasks between the worker and the robot, leading to a new form of human-machine interaction that may impact the meaning and the quality of work for the employee.
While progresses have been made towards making robot programming easier, it still often requires expert knowledge with most of the interaction being pre-defined. The operator must follow the machine’s protocol, making the interaction unrewarding. New progresses in machine learning such as learning from demonstration allow for the user to tailor the interaction with the robot to its needs. However, intuitive user interfaces to these algorithms are still missing. The project aims at bridging this gap by developing interfaces for adaptive human-robot collaboration for the industry. A worker-centered approach will be taken, with operators from different fields of industry participating in the design of the robotic system.
Scientific studies show that the evaluation and acceptance of robots is socially and culturally influenced and varies according to the situation. The project takes these insights into account by first observing the situational practices of human-machine interactions and then reflecting and further deepening them in interviews with employees. In this way, both socio-cultural and situational practices and work experiences can be worked out.
In a longitudinal design, the effects of the introduction of cobots on the work culture, the demands on the work activity and the subjective work experience of the employees will be investigated. The project deals with the ethical implications of the use of cobots and the definition of "good work" in the age of digitization.
Based on these findings, and through participatory design, a robotic system will be developed that strives to foster empowering human-robot interactions for the operator. The user shall be able to easily communicate his/her needs to the robot, to understand the behavior of the robot in order to control it and to easily adapt its behavior to the requirements of the task.
On the basis of three concrete practical cases, a general, flexible robotic solution is developed that aims at fostering empowering human-robot interactions, while maintaining industrial productivity and quality requirements. The system is developed together with the operators during two implementations cycles. It is constantly tested by the users and adapted to their needs in order to ensure efficient, rewarding interactions.
In addition, the project examines the effects of cobots on work culture, the demands on work activity and the subjective work experience. We start from a human-machine understanding that is not deterministic but relational. The project aims to identify the conditions, attitudes and skills that can lead to automation, leading to an appreciation of work and higher self-esteem among employees.