Publications

Conference papers, journal articles, and dissertations.

Preprints
Fundamental Limits for Sensor-Based Control via the Gibbs Variational Principle
V. Pacelli, E. A. Theodorou
In Preparation
In Preparation
2026
Sampling-Based Control via Entropy-Regularized Optimal Transport
V. Pacelli, A. Ratheesh, E. A. Theodorou
Proceedings of Robotics: System and Science
Submitted; Under Review
Distributionally Robust Schrödinger Bridge
J. Sul, P. Theodoropoulos, V. Pacelli, J. Choi, E. A. Theodorou
Proceedings of the International Conference on Machine Learning
Submitted; Under Review
2025
Operator Splitting Covariance Steering for Safe Stochastic Nonlinear Control
A. Ratheesh, V. Pacelli, A. D. Saravanos, E. A. Theodorou
Proceedings of the Conference on Decision and Control
MetroSky: High-Fidelity Photorealistic Simulator for Urban Air Mobility Vehicles
A. Ratheesh, V. Pacelli, E. A. Theodorou
SCITECH Forum
Deep Distributed Optimization for Large-Scale Quadratic Programming
A. D. Saravanos, H. Kuperman, A. Oshin, A. T. Abdul, V. Pacelli, E. Theodorou
Proceedings of the International Conference on Learning Representations
DOI arXiv
Feedback Schrödinger Bridge Matching
P. Theodoropoulos, N. Komianos, V. Pacelli, G.-H. Liu, E. A. Theodorou
Proceedings of the International Conference on Learning Representations
Oral DOI arXiv
2022
Fundamental Performance Limits for Sensor-Based Robot Control and Policy Learning
A. Majumdar, V. Pacelli
Proceedings of Robotics: System and Science
Robust Control Under Uncertainty via Bounded Rationality and Differential Privacy
V. Pacelli, A. Majumdar
Proceedings of the International Conference on Robotics and Automation, pp. 3467--3474
DOI arXiv
2021
Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning
A. Sonar, V. Pacelli, A. Majumdar
Proceedings of the Conference on Learning for Dynamics and Control, pp. 21--33
arXiv
2020
Learning Task-Driven Control Policies via Information Bottlenecks
V. Pacelli, A. Majumdar
Proceedings of Robotics: System and Science
2019
Task-Driven Estimation and Control via Information Bottlenecks
V. Pacelli, A. Majumdar
Proceedings of the International Conference on Robotics and Automation, pp. 2061--2067
DOI
2018
Integration of Local Geometry and Metric Information in Sampling-Based Motion Planning
V. Pacelli, O. Arslan, D. E. Koditschek
Proceedings of the International Conference on Robotics and Automation, pp. 3061--3068
2017
Sensory Steering for Sampling-Based Motion Planning
O. Arslan, V. Pacelli, D. E. Koditschek
Proceedings of the International Conference on Intelligent Robots and Systems, pp. 3708--3715
Journal Articles
Fundamental Limits for Sensor-Based Robot Control
A. Majumdar, Z. Mei, V. Pacelli
International Journal of Robotics Research, vol. 42, no. 12, pp. 1051--1069
DOI arXiv
Patent
Systems of Stacking Interlocking Blocks
R. Mangharam, M. E. O'Kelly, V. Pacelli, M. A. Brady
U.S. Patent 11,213,747
U.S. Patent 11,213,747
Dissertations
Information-Theoretic Necessary and Sufficient Conditions for the Task-Driven Control of Robots
V. Pacelli
Ph.D. Dissertation, Princeton University, 2023
Joint Exploration of Local Metrics and Geometry in Sampling-Based Planning
V. Pacelli
M.S. Thesis, University of Pennsylvania, 2017