7 citations · 8 across the 6 of their papers we have counts for
6 papers
Q-learning-based Model-free Safety Filter
Guo Ning Sue, Yogita Choudhary, Richard Desatnik +3
Ensuring safety via safety filters in real-world robotics presents significant challenges, particularly when the system dynamics is complex or unavailable. To handle this issue, le…
Agile Continuous Jumping in Discontinuous Terrains
Yuxiang Yang, Guanya Shi, Changyi Lin +8
We focus on agile, continuous, and terrain-adaptive jumping of quadrupedal robots in discontinuous terrains such as stairs and stepping stones. Unlike single-step jumping, continuo…
Model Predictive Control for Aggressive Driving Over Uneven Terrain
Tyler Han, Alex Liu, Anqi Li +3
Terrain traversability in unstructured off-road autonomy has traditionally relied on semantic classification, resource-intensive dynamics models, or purely geometry-based methods t…
Deep Model Predictive Optimization
Jacob Sacks, Rwik Rana, Kevin Huang +3
A major challenge in robotics is to design robust policies which enable complex and agile behaviors in the real world. On one end of the spectrum, we have model-free reinforcement…
DATT: Deep Adaptive Trajectory Tracking for Quadrotor Control
Kevin Huang, Rwik Rana, Alexander Spitzer +2
Precise arbitrary trajectory tracking for quadrotors is challenging due to unknown nonlinear dynamics, trajectory infeasibility, and actuation limits. To tackle these challenges, w…
Safe Deep Policy Adaptation
Wenli Xiao, Tairan He, John Dolan +1
A critical goal of autonomy and artificial intelligence is enabling autonomous robots to rapidly adapt in dynamic and uncertain environments. Classic adaptive control and safe cont…