146 citations · 176 across the 17 of their papers we have counts for
6 papers · 1 filter
Adversarial Robustness with Semi-Infinite Constrained Learning
Alexander Robey, Luiz F. O. Chamon, George J. Pappas +2
Despite strong performance in numerous applications, the fragility of deep learning to input perturbations has raised serious questions about its use in safety-critical domains. Wh…
Coverage Control in Multi-Robot Systems via Graph Neural Networks
Walker Gosrich, Siddharth Mayya, Rebecca Li +4
This paper develops a decentralized approach to mobile sensor coverage by a multi-robot system. We consider a scenario where a team of robots with limited sensing range must positi…
Composable Learning with Sparse Kernel Representations
Ekaterina Tolstaya, Ethan Stump, Alec Koppel +1
We present a reinforcement learning algorithm for learning sparse non-parametric controllers in a Reproducing Kernel Hilbert Space. We improve the sample complexity of this approac…
Stability of Neural Networks on Riemannian Manifolds
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro
Convolutional Neural Networks (CNNs) have been applied to data with underlying non-Euclidean structures and have achieved impressive successes. This brings the stability analysis o…
Learning Connectivity for Data Distribution in Robot Teams
Ekaterina Tolstaya, Landon Butler, Daniel Mox +3
Many algorithms for control of multi-robot teams operate under the assumption that low-latency, global state information necessary to coordinate agent actions can readily be dissem…
Large Scale Distributed Collaborative Unlabeled Motion Planning with Graph Policy Gradients
Arbaaz Khan, Vijay Kumar, Alejandro Ribeiro
In this paper, we present a learning method to solve the unlabelled motion problem with motion constraints and space constraints in 2D space for a large number of robots. To solve…