53 citations · 114 across the 7 of their papers we have counts for
8 papers
H-GAP: Humanoid Control with a Generalist Planner
Zhengyao Jiang, Yingchen Xu, Nolan Wagener +5
Humanoid control is an important research challenge offering avenues for integration into human-centric infrastructures and enabling physics-driven humanoid animations. The dauntin…
TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation
Xiangyun Meng, Nathan Hatch, Alexander Lambert +11
Effective use of camera-based vision systems is essential for robust performance in autonomous off-road driving, particularly in the high-speed regime. Despite success in structure…
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri +3
Simulated humanoids are an appealing research domain due to their physical capabilities. Nonetheless, they are also challenging to control, as a policy must drive an unstable, disc…
Consistent Dropout for Policy Gradient Reinforcement Learning
Matthew Hausknecht, Nolan Wagener
Dropout has long been a staple of supervised learning, but is rarely used in reinforcement learning. We analyze why naive application of dropout is problematic for policy-gradient…
Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
Many sequential decision problems involve finding a policy that maximizes total reward while obeying safety constraints. Although much recent research has focused on the developmen…
An Online Learning Approach to Model Predictive Control
Nolan Wagener, Ching-An Cheng, Jacob Sacks +1
Model predictive control (MPC) is a powerful technique for solving dynamic control tasks. In this paper, we show that there exists a close connection between MPC and online learnin…
Fast Policy Learning through Imitation and Reinforcement
Ching-An Cheng, Xinyan Yan, Nolan Wagener +1
Imitation learning (IL) consists of a set of tools that leverage expert demonstrations to quickly learn policies. However, if the expert is suboptimal, IL can yield policies with i…
Learning Contact-Rich Manipulation Skills with Guided Policy Search
Sergey Levine, Nolan Wagener, Pieter Abbeel
Autonomous learning of object manipulation skills can enable robots to acquire rich behavioral repertoires that scale to the variety of objects found in the real world. However, cu…