Papers
959 papers found
Deep Dynamics Models for Learning Dexterous Manipulation
Anusha Nagabandi, Kurt Konolige, Sergey Levine et al.
Deep Value Model Predictive Control
David Hoeller, Farbod Farshidian, Marco Hutter
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Ajay Jain, Sergio Casas, Renjie Liao et al.
Disentangled Relational Representations for Explaining and Learning from Demonstration
Yordan Hristov, Daniel Angelov, Michael Burke et al.
Dynamic Experience Replay
Jieliang Luo, Hui Li
Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation
Kuan Fang, Yuke Zhu, Animesh Garg et al.
End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds
Yin Zhou, Pei Sun, Yu Zhang et al.
Energy-efficient Path Planning for Ground Robots by and Combining Air and Ground Measurements
Minghan Wei, Volkan Isler
Entity Abstraction in Visual Model-Based Reinforcement Learning
Rishi Veerapaneni, John D. Co-Reyes, Michael Chang et al.
Experience-Embedded Visual Foresight
Lin Yen-Chen, Maria Bauza, Phillip Isola
Graph Policy Gradients for Large Scale Robot Control
Arbaaz Khan, Ekaterina Tolstaya, Alejandro Ribeiro et al.
Graph-Structured Visual Imitation
Maximilian Sieb, Zhou Xian, Audrey Huang et al.
HJB Optimal Feedback Control with Deep Differential Value Functions and Action Constraints
Michael Lutter, Boris Belousov, Kim Listmann et al.
HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators
Chengshu Li, Fei Xia, Roberto Martín-Martín et al.
Hybrid system identification using switching density networks
Michael Burke, Yordan Hristov, Subramanian Ramamoorthy
Identifying Unknown Instances for Autonomous Driving
Kelvin Wong, Shenlong Wang, Mengye Ren et al.
Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models
Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki et al.
Inferring Task Goals and Constraints using Bayesian Nonparametric Inverse Reinforcement Learning
Daehyung Park, Michael Noseworthy, Rohan Paul et al.
Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction
Weiming Zhi, Lionel Ott, Fabio Ramos
Language-guided Semantic Mapping and Mobile Manipulation in Partially Observable Environments
Siddharth Patki, Ethan Fahnestock, Thomas M. Howard et al.
Learning by Cheating
Dian Chen, Brady Zhou, Vladlen Koltun et al.
Learning Compact Models for Planning with Exogenous Processes
Rohan Chitnis, Tomás Lozano-Pérez
Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks
Ekaterina Tolstaya, Fernando Gama, James Paulos et al.
Learning from demonstration with model-based Gaussian process
Noémie Jaquier, David Ginsbourger, Sylvain Calinon
Learning from My Partner’s Actions: Roles in Decentralized Robot Teams
Dylan P. Losey, Mengxi Li, Jeannette Bohg et al.