Matthew Tsao — accepted AI-conference papers

2020

Sample Complexity of Probabilistic Roadmaps via ε-nets

Matthew Tsao, Kiril Solovey, Marco Pavone

ICRA 2020poster

We study fundamental theoretical aspects of probabilistic roadmaps (PRM) in the finite time (non-asymptotic) regime. In particular, we investigate how completeness and optimality guarantees of the approach are influenced by the underlying deterministic sampling distribution X and connection radius r…

Cited by 22 Source ↗Scholar ↗

2019

Model Predictive Control of Ride-sharing Autonomous Mobility-on-Demand Systems

Matthew Tsao, Dejan Milojevic, Claudio Ruch, Mauro Salazar, Emilio Frazzoli, Marco Pavone

ICRA 2019poster

This paper presents a model predictive control (MPC) approach to optimize routes for Ride-sharing Autonomous Mobility-on-Demand (RAMoD) systems, whereby self-driving vehicles provide coordinated on-demand mobility, possibly allowing multiple customers to share a ride. Specifically, we first devise a…

Cited by 103 Source ↗Scholar ↗