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Outputs (2)

A corroborative approach to verification and validation of human–robot teams (2019)
Journal Article
Webster, M., Western, D., Araiza-Illan, D., Dixon, C., Eder, K., Fisher, M., & Pipe, A. G. (2020). A corroborative approach to verification and validation of human–robot teams. International Journal of Robotics Research, 39(1), 73-99. https://doi.org/10.1177/0278364919883338

© The Author(s) 2019. We present an approach for the verification and validation (V&V) of robot assistants in the context of human–robot interactions, to demonstrate their trustworthiness through corroborative evidence of their safety and functional... Read More about A corroborative approach to verification and validation of human–robot teams.

Feed-forward selection of cerebellar models for calibration of robot sound source localization (2019)
Conference Proceeding
Baxendale, M. D., Nibouche, M., Secco, E. L., Pipe, A. G., & Pearson, M. J. (2019). Feed-forward selection of cerebellar models for calibration of robot sound source localization. https://doi.org/10.1007/978-3-030-24741-6_1

© 2019, Springer Nature Switzerland AG. We present a responsibility predictor, based on the adaptive filter model of the cerebellum, to provide feed-forward selection of cerebellar calibration models for robot Sound Source Localization (SSL), based o... Read More about Feed-forward selection of cerebellar models for calibration of robot sound source localization.