7 citations · 13 across the 7 of their papers we have counts for
4 papers · 1 filter
PaRCE: Probabilistic and Reconstruction-based Competency Estimation for CNN-based Image Classification
Sara Pohland, Claire Tomlin
Convolutional neural networks (CNNs) are extremely popular and effective for image classification tasks but tend to be overly confident in their predictions. Various works have sou…
Competency-Aware Planning for Probabilistically Safe Navigation Under Perception Uncertainty
Sara Pohland, Claire Tomlin
Perception-based navigation systems are useful for unmanned ground vehicle (UGV) navigation in complex terrains, where traditional depth-based navigation schemes are insufficient.…
Understanding the Dependence of Perception Model Competency on Regions in an Image
Sara Pohland, Claire Tomlin
While deep neural network (DNN)-based perception models are useful for many applications, these models are black boxes and their outputs are not yet well understood. To confidently…
Stranger Danger! Identifying and Avoiding Unpredictable Pedestrians in RL-based Social Robot Navigation
Sara Pohland, Alvin Tan, Prabal Dutta +1
Reinforcement learning (RL) methods for social robot navigation show great success navigating robots through large crowds of people, but the performance of these learning-based met…