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Introspective Robot Perception using Smoothed Predictions from Bayesian Neural Networks
This work focuses on improving uncertainty estimation in the field of object classification from RGB images and demonstrates its benefits in two robotic applications.
Amortized Object and Scene Perception for Long-term Robot Manipulation
Mobile robots, performing long-term manipulation activities in human environments, have to perceive a wide variety of objects possessing very different visual characteristics and need to reliably keep track of these throughout the execution of a task.
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