290 citations · 1.5k across the 41 of their papers we have counts for
14 papers · 1 filter
CaRT: Certified Safety and Robust Tracking in Learning-based Motion Planning for Multi-Agent Systems
Hiroyasu Tsukamoto, Benjamin Rivière, Changrak Choi +2
The key innovation of our analytical method, CaRT, lies in establishing a new hierarchical, distributed architecture to guarantee the safety and robustness of a given learning-base…
Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds
Michael O'Connell, Guanya Shi, Xichen Shi +4
Executing safe and precise flight maneuvers in dynamic high-speed winds is important for the ongoing commoditization of uninhabited aerial vehicles (UAVs). However, because the rel…
Learning-based methods to model small body gravity fields for proximity operations: Safety and Robustness
Daniel Neamati, Yashwanth Kumar Nakka, Soon-Jo Chung
Accurate gravity field models are essential for safe proximity operations around small bodies. State-of-the-art techniques use spherical harmonics or high-fidelity polyhedron shape…
Trajectory Optimization of Chance-Constrained Nonlinear Stochastic Systems for Motion Planning Under Uncertainty
Yashwanth Kumar Nakka, Soon-Jo Chung
We present gPC-SCP: Generalized Polynomial Chaos-based Sequential Convex Programming to compute a sub-optimal solution for a continuous-time chance-constrained stochastic nonlinear…
Neural Tree Expansion for Multi-Robot Planning in Non-Cooperative Environments
Benjamin Riviere, Wolfgang Hoenig, Matthew Anderson +1
We present a self-improving, Neural Tree Expansion (NTE) method for multi-robot online planning in non-cooperative environments, where each robot attempts to maximize its cumulativ…
Meta-Learning-Based Robust Adaptive Flight Control Under Uncertain Wind Conditions
Michael O'Connell, Guanya Shi, Xichen Shi +1
Realtime model learning proves challenging for complex dynamical systems, such as drones flying in variable wind conditions. Machine learning technique such as deep neural networks…