Methodological Approach for the Evaluation of an Adaptive and Assistive Human-Machine System
Lorenzo Sabattini, Valeria Villani, Julia N. Czerniak, Frieder Loch, Alexander Mertens, Birgit Vogel-Heuser, Cesare Fantuzzi
- Year
- 2018
- Access
- Open access
Abstract
With the increasing complexity of modern industrial automatic and robotic systems, an increasing burden is put on the operators, who are requested to supervise and interact with such complex systems, typically under challenging and stressful conditions. To overcome this issue, it is necessary to adopt a responsible approach based on the anthropocentric design methodology, such that machines adapt to the humans capabilities. Moving along these lines, a methodological approach called MATE was introduced in [1], which consists in devising complex automatic or robotic solutions that measure current operator's status, adapting the interaction accordingly, and providing her/him with proper training to improve the interaction and learn lacking skills and expertise. In this paper we propose an evaluation and validation procedure to guarantee the achievement of the requirements of a MATE system.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992