67 citations · 68 across the 14 of their papers we have counts for
4 papers · 1 filter
Model-Based Control with Sparse Neural Dynamics
Ziang Liu, Genggeng Zhou, Jeff He +4
Learning predictive models from observations using deep neural networks (DNNs) is a promising new approach to many real-world planning and control problems. However, common DNNs ar…
Approximating Robot Configuration Spaces with few Convex Sets using Clique Covers of Visibility Graphs
Peter Werner, Alexandre Amice, Tobia Marcucci +2
Many computations in robotics can be dramatically accelerated if the robot configuration space is described as a collection of simple sets. For example, recently developed motion p…
On the Sample Complexity of Imitation Learning for Smoothed Model Predictive Control
Daniel Pfrommer, Swati Padmanabhan, Kwangjun Ahn +4
Recent work in imitation learning has shown that having an expert controller that is both suitably smooth and stable enables stronger guarantees on the performance of the learned c…
Fast Path Planning Through Large Collections of Safe Boxes
Tobia Marcucci, Parth Nobel, Russ Tedrake +1
We present a fast algorithm for the design of smooth paths (or trajectories) that are constrained to lie in a collection of axis-aligned boxes. We consider the case where the numbe…