Papers
1,468 papers found
DensePhysNet: Learning Dense Physical Object Representations Via Multi-Step Dynamic Interactions
Zhenjia Xu, Jiajun Wu, Andy Zeng et al.
DESPOT-Alpha: Online POMDP Planning with Large State and Observation Spaces
Neha Priyadarshini Garg, David Hsu, Wee Sun Lee
Differentiable Algorithm Networks for Composable Robot Learning
Peter Karkus, Xiao Ma, David Hsu et al.
Direct Drive Hands: Force-Motion Transparency in Gripper Design
Ankit Bhatia, Aaron Johnson, Matthew T. Mason
DIViS: Domain Invariant Visual Servoing for Collision-Free Goal Reaching
Fereshteh Sadeghi
Efficient Algorithms for Optimal Perimeter Guarding
Si Wei Feng, Shuai D. Han, Kai Gao et al.
End-To-End Robotic Reinforcement Learning without Reward Engineering
Avi Singh, Larry Yang, Chelsea Finn et al.
Equivalence of the Projected Forward Dynamics and the Dynamically Consistent Inverse Solution
Joao Moura, Vladimir Ivan, Mustafa Suphi Erden et al.
From Explanation to Synthesis: Compositional Program Induction for Learning from Demonstration
Michael Burke, Svetlin Valentinov Penkov, Subramanian Ramamoorthy
Game Theoretic Planning for Self-Driving Cars in Competitive Scenarios
Mingyu Wang, Zijian Wang, John Talbot et al.
Harnessing Reinforcement Learning for Neural Motion Planning
Tom Jurgenson, Aviv Tamar
Highly Parallelized Data-Driven MPC for Minimal Intervention Shared Control
Alexander Broad, Todd Murphey, Brenna Argall
High-Throughput Computation of Shannon Mutual Information on Chip
Peter Zhi Xuan Li, Zhengdong Zhang, Sertac Karaman et al.
Idiothetic Verticality Estimation through Head Stabilization Strategy
Ildar Farkhatdinov, Hannah Michalska, Alain Berthoz et al.
Impact-Friendly Robust Control Design with Task-Space Quadratic Optimization
Yuquan Wang, Abderrahmane Kheddar
Improvisation through Physical Understanding: Using Novel Objects As Tools with Visual Foresight
Annie Xie, Frederik Ebert, Sergey Levine et al.
Influencing Leading and Following in Human-Robot Teams
Minae Kwon, Mengxi Li, Alexandre Bucquet et al.
Inverting Learned Dynamics Models for Aggressive Multirotor Control
Alexander Spitzer, Nathan Michael
Learning Deep Stochastic Optimal Control Policies Using Forward-Backward SDEs
Ziyi Wang, Marcus Pereira, Ioannis Exarchos et al.
Learning Reward Functions by Integrating Human Demonstrations and Preferences
Malayandi Palan, Gleb Shevchuk, Nicholas Charles Landolfi et al.
Learning Robotic Manipulation through Visual Planning and Acting
Angelina Wang, Thanard Kurutach, Kara Liu et al.
Learning to Plan with Logical Automata
Brandon Araki, Kiran Vodrahalli, Thomas Leech et al.
Learning to Walk Via Deep Reinforcement Learning
Tuomas Haarnoja, Sehoon Ha, Aurick Zhou et al.
LeTS-Drive: Driving in a Crowd by Learning from Tree Search
Panpan Cai, Yuanfu Luo, Aseem Saxena et al.
Leveraging Experience in Lazy Search
Mohak Bhardwaj, Sanjiban Choudhury, Byron Boots et al.