Papers
Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics
Michael Neunert, Abbas Abdolmaleki, Markus Wulfmeier et al.
AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers
Andrey Kurenkov, Ajay Mandlekar, Roberto Martin-Martin et al.
Stochastic Optimal Control as Approximate Input Inference
Joe Watson, Hany Abdulsamad, Jan Peters
Provably Robust Blackbox Optimization for Reinforcement Learning
Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder et al.
Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks
Ekaterina Tolstaya, Fernando Gama, James Paulos et al.
Connectivity Guaranteed Multi-robot Navigation via Deep Reinforcement Learning
Juntong Lin, Xuyun Yang, Peiwei Zheng et al.
Multi-Frame GAN: Image Enhancement for Stereo Visual Odometry in Low Light
Eunah Jung, Nan Yang, Daniel Cremers
HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints
Michael Lutter, Boris Belousov, Kim Listmann et al.
A Learnable Safety Measure
Steve Heim, Alexander von Rohr, Sebastian Trimpe et al.
Learning Navigation Subroutines from Egocentric Videos
Ashish Kumar, Saurabh Gupta, Jitendra Malik
HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators
Chengshu Li, Fei Xia, Roberto Martín-Martín et al.
PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning
Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing
Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models
Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki et al.
Adversarial Active Exploration for Inverse Dynamics Model Learning
Zhang-Wei Hong, Tsu-Jui Fu, Tzu-Yun Shann et al.
Conditional Driving from Natural Language Instructions
Junha Roh, Chris Paxton, Andrzej Pronobis et al.
Contextual Imagined Goals for Self-Supervised Robotic Learning
Ashvin Nair, Shikhar Bahl, Alexander Khazatsky et al.
Self-Paced Contextual Reinforcement Learning
Pascal Klink, Hany Abdulsamad, Boris Belousov et al.
Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances
Vitor Guizilini, Jie Li, Rares Ambrus et al.
Learning to Manipulate Object Collections Using Grounded State Representations
Matthew Wilson, Tucker Hermans
A Survey on Reproducibility by Evaluating Deep Reinforcement Learning Algorithms on Real-World Robots
Nicolai A. Lynnerup, Laura Nolling, Rasmus Hasle et al.
Bayesian Optimization in Variational Latent Spaces with Dynamic Compression
Rika Antonova, Akshara Rai, Tianyu Li et al.
TuneNet: One-Shot Residual Tuning for System Identification and Sim-to-Real Robot Task Transfer
Adam Allevato, Elaine Schaertl Short, Mitch Pryor et al.
Leveraging exploration in off-policy algorithms via normalizing flows
Bogdan Mazoure, Thang Doan, Audrey Durand et al.
Combining Optimal Control and Learning for Visual Navigation in Novel Environments
Somil Bansal, Varun Tolani, Saurabh Gupta et al.
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Ajay Jain, Sergio Casas, Renjie Liao et al.