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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Notes
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A lexical database of English words started in 1985 to support text analysis and NLP.
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Acknowledgements
We thank the organizers of ISRR2019, in Hanoi, for the invitation to present a first pass of these ideas in a Distinguished Talk. This research was conducted by the Australian Research Council Centre of Excellence for Robotic Vision (project number CE140100016).
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Corke, P., Dayoub, F., Hall, D., Skinner, J., Sünderhauf, N. (2022). What Can Robotics Research Learn from Computer Vision Research?. In: Asfour, T., Yoshida, E., Park, J., Christensen, H., Khatib, O. (eds) Robotics Research. ISRR 2019. Springer Proceedings in Advanced Robotics, vol 20. Springer, Cham. https://doi.org/10.1007/978-3-030-95459-8_61
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