Nolan Wagener
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View article: H-GAP: Humanoid Control with a Generalist Planner
H-GAP: Humanoid Control with a Generalist Planner Open
Humanoid control is an important research challenge offering avenues for integration into human-centric infrastructures and enabling physics-driven humanoid animations. The daunting challenges in this field stem from the difficulty of opti…
View article: TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation
TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation Open
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 structured, on-road settings, current end-to-end approaches for scene…
View article: TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation
TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation Open
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 structured, on-road settings, current end-to-end approaches for scen…
View article: MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control Open
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, discontinuous, and high-dimensional physical system. One widely…
View article: Consistent Dropout for Policy Gradient Reinforcement Learning
Consistent Dropout for Policy Gradient Reinforcement Learning Open
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 learning algorithms and introduce consistent dropout, a sim…
View article: Safe Reinforcement Learning Using Advantage-Based Intervention
Safe Reinforcement Learning Using Advantage-Based Intervention Open
Many sequential decision problems involve finding a policy that maximizes total reward while obeying safety constraints. Although much recent research has focused on the development of safe reinforcement learning (RL) algorithms that produ…
View article: An Online Learning Approach to Model Predictive Control
An Online Learning Approach to Model Predictive Control Open
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 learning, an abstract theoretical framework for analyzing online d…
View article: Fast Policy Learning through Imitation and Reinforcement
Fast Policy Learning through Imitation and Reinforcement Open
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 inferior performance compared to reinforcement learning (RL)…
View article: Learning Contact-Rich Manipulation Skills with Guided Policy Search
Learning Contact-Rich Manipulation Skills with Guided Policy Search Open
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, current motion skill learning methods typically restrict the …