research
∙
01/27/2023
Tree-structured Policy Planning with Learned Behavior Models
Autonomous vehicles (AVs) need to reason about the multimodal behavior o...
share
research
∙
12/13/2022
DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles
Autonomous vehicle (AV) stacks are typically built in a modular fashion,...
research
∙
10/26/2022
Planning with Occluded Traffic Agents using Bi-Level Variational Occlusion Models
Reasoning with occluded traffic agents is a significant open challenge f...
research
∙
05/17/2021
Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation
Simultaneous localization and mapping (SLAM) remains challenging for a n...
research
∙
10/03/2020
Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban
Intelligent robots need to achieve abstract objectives using concrete, s...
research
∙
09/11/2020
Physically Embedded Planning Problems: New Challenges for Reinforcement Learning
Recent work in deep reinforcement learning (RL) has produced algorithms ...
research
∙
05/19/2020
Differentiable Mapping Networks: Learning Structured Map Representations for Sparse Visual Localization
Mapping and localization, preferably from a small number of observations...
research
∙
02/23/2020
Discriminative Particle Filter Reinforcement Learning for Complex Partial Observations
Deep reinforcement learning is successful in decision making for sophist...
research
∙
05/30/2019
Particle Filter Recurrent Neural Networks
Recurrent neural networks (RNNs) have been extraordinarily successful fo...
research
∙
05/28/2019
Differentiable Algorithm Networks for Composable Robot Learning
This paper introduces the Differentiable Algorithm Network (DAN), a comp...
research
∙
07/17/2018
Integrating Algorithmic Planning and Deep Learning for Partially Observable Navigation
We propose to take a novel approach to robot system design where each bu...
research
∙
05/23/2018
Particle Filter Networks with Application to Visual Localization
Particle filtering is a powerful method for sequential state estimation ...
research
∙
05/23/2018
Particle Filter Networks: End-to-End Probabilistic Localization From Visual Observations
Particle filters sequentially approximate posterior distributions by sam...
research
∙
03/20/2017
QMDP-Net: Deep Learning for Planning under Partial Observability
This paper introduces the QMDP-net, a neural network architecture for pl...
research
∙
12/06/2016
