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Fit for Purpose? Predicting Perception Performance Based on Past Experience.

, , and . ISER, volume 1 of Springer Proceedings in Advanced Robotics, page 454-464. Springer, (2016)

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Exploiting domain knowledge for Object Discovery., , , , and . ICRA, page 2118-2125. IEEE, (2013)Know your limits: Embedding localiser performance models in teach and repeat maps., , , , and . ICRA, page 4238-4244. IEEE, (2015)Dropout Distillation for Efficiently Estimating Model Confidence., , and . CoRR, (2018)Urban Driving with Conditional Imitation Learning., , , , , , , , , and 1 other author(s). ICRA, page 251-257. IEEE, (2020)Scheduled perception for energy-efficient path following., , , , and . ICRA, page 4799-4806. IEEE, (2015)Fit for Purpose? Predicting Perception Performance Based on Past Experience., , and . ISER, volume 1 of Springer Proceedings in Advanced Robotics, page 454-464. Springer, (2016)Enabling intelligent energy management for robots using publicly available maps., , , and . IROS, page 2224-2229. IEEE, (2016)Urban Driving with Conditional Imitation Learning., , , , , , , , , and 1 other author(s). CoRR, (2019)HerbDisc: Towards lifelong robotic object discovery., , , , and . Int. J. Robotics Res., 34 (1): 3-25 (2015)Wrong Today, Right Tomorrow: Experience-Based Classification for Robot Perception., , , and . FSR, volume 113 of Springer Tracts in Advanced Robotics, page 173-186. Springer, (2015)