Tracking work task completion
A support vector machine approach for assisting workbenches
DOI:
https://doi.org/10.17560/atp.v59i11.1911Keywords:
machine learning, assisting workbench, human-machine interaction, 3D depth camera, robust tracking of task completionAbstract
Tightening quality requirements of industrial products involving manual assembly lead to the development of assisting workbenches with integrated functions to support workers performing these manual tasks. This contribution discusses a new approach to learning transitions of a finite state automaton representing the sequence of work tasks based on the video stream of a 3D depth camera. Preprocessed video data is fed into a three-stage classification scheme based on support vector machines. The results of the classification are then related to the state automation to trigger state transitions indicating the completion of a specific work task and the start of the next one. The proposed approach has been evaluated at an industrial assembly process of moderate complexity and shows very robust results with respect to disturbances caused by inaccurate object classification.
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