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Building Safe Autonomy

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Tue, 09/28/2021

Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances
Planning in Dynamic and Partially Unknown Environments
Controller synthesis for linear system with reach-avoid specifications
Learning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates
Density Constrained Reinforcement Learning
Uncertainty-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric
Optimal mixed discrete-continuous planning for linear hybrid systems
Fast and Guaranteed Safe Controller Synthesis for Aerial Vehicle Models
Learning Certified Control using Contraction Metric
Multi-agent safety verification using symmetry transformations