Autonomous vehicles (AVs) need to reason about the multimodal behavior o...
Autonomous vehicle (AV) stacks are typically built in a modular fashion,...
Reasoning with occluded traffic agents is a significant open challenge f...
Simultaneous localization and mapping (SLAM) remains challenging for a n...
Intelligent robots need to achieve abstract objectives using concrete,
s...
Recent work in deep reinforcement learning (RL) has produced algorithms
...
Mapping and localization, preferably from a small number of observations...
Deep reinforcement learning is successful in decision making for
sophist...
Recurrent neural networks (RNNs) have been extraordinarily successful fo...
This paper introduces the Differentiable Algorithm Network (DAN), a
comp...
We propose to take a novel approach to robot system design where each
bu...
Particle filtering is a powerful method for sequential state estimation ...
Particle filters sequentially approximate posterior distributions by sam...
This paper introduces the QMDP-net, a neural network architecture for
pl...
Scarce data is a major challenge to scaling robot learning to truly comp...