What Can Robotics Research Learn from Computer Vision Research?
Date
2022
Authors
Corke, P.
Dayoub, F.
Hall, D.
Skinner, J.
Sünderhauf, N.
Editors
Asfour, T.
Yoshida, E.
Park, J.
Christensen, H.
Khatib, O.
Yoshida, E.
Park, J.
Christensen, H.
Khatib, O.
Advisors
Journal Title
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Volume Title
Type:
Conference paper
Citation
Proceedings of the 19th International Symposium of Robotic Research (ISRR 2019), as published in Springer Proceedings in Advanced Robotics, 2022 / Asfour, T., Yoshida, E., Park, J., Christensen, H., Khatib, O. (ed./s), vol.20, pp.987-1003
Statement of Responsibility
Peter Corke, Feras Dayoub, David Hall, John Skinner, Niko Sünderhauf
Conference Name
International Symposium of Robotic Research (ISRR) (6 Oct 2019 - 10 Oct 2019 : Hanoi, Vietnam)
Abstract
The fields of computer vision and robotics are both children of the artificial intelligence program that was spawned by the Dartmouth Conference in 1956. In recent decades the fields have diverged in terms of conferences and journals, research methodology and research rate. From a robotics perspective it seems that computer vision is in the fast lane while robotics is stuck in the slow lane. Roboticists hold a fundamental belief in the importance of experimentation but could it be that experiments are actually holding us back? Or is it that we are doing experiments poorly?
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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG