11 citations · 15 across the 3 of their papers we have counts for
12 papers
Learning-based Initialization Strategy for Safety of Multi-Vehicle Systems
Jennifer C. Shih, Akshara Rai, Laurent El Ghaoui
Multi-vehicle collision avoidance is a highly crucial problem due to the soaring interests of introducing autonomous vehicles into the real world in recent years. The safety of the…
Leveraging Forward Model Prediction Error for Learning Control
Sarah Bechtle, Bilal Hammoud, Akshara Rai +2
Learning for model based control can be sample-efficient and generalize well, however successfully learning models and controllers that represent the problem at hand can be challen…
Learning Navigation Skills for Legged Robots with Learned Robot Embeddings
Joanne Truong, Denis Yarats, Tianyu Li +4
Recent work has shown results on learning navigation policies for idealized cylinder agents in simulation and transferring them to real wheeled robots. Deploying such navigation po…
Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion
Tianyu Li, Roberto Calandra, Deepak Pathak +3
Hierarchical learning has been successful at learning generalizable locomotion skills on walking robots in a sample-efficient manner. However, the low-dimensional "latent" action u…
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization
Benjamin Letham, Roberto Calandra, Akshara Rai +1
Bayesian optimization (BO) is a popular approach to optimize expensive-to-evaluate black-box functions. A significant challenge in BO is to scale to high-dimensional parameter spac…
Encoding Physical Constraints in Differentiable Newton-Euler Algorithm
Giovanni Sutanto, Austin S. Wang, Yixin Lin +4
The recursive Newton-Euler Algorithm (RNEA) is a popular technique for computing the dynamics of robots. RNEA can be framed as a differentiable computational graph, enabling the dy…