Publications · ScalAR Lab


Publications

Research from the ScalAR Lab spanning multi-robot systems, learning complex dynamics, learning-based control, adaptive sampling, and autonomous systems in geophysical environments.

PreprintsUnder review
Preprint

Physics-informed sensor coverage through structure preserving machine learning
B. D. Shaffer, B. Kinch, J. Klobusicky, M. A. Hsieh, N. Trask
Under review — SIAM Journal on Scientific Computing
arXiv

Preprint

Sensitivity Bottlenecks on Transformers for Control Sequence Modeling
H. Yu, K. Mao, M. Taylor, R. Zhang, M. A. Hsieh, V. Kumar, S. Gao
Submitted to NeurIPS 2026, Sydney, Australia
arXiv

Preprint

Learned Lagrangian Models of PDEs via Euler–Lagrange Residual Minimization
L. Zhornyak, E. Forgoston, and M. A. Hsieh
Submitted to NeurIPS 2026, Sydney, Australia
arXiv

Preprint

A Meshfree Exterior Calculus for Generalizable and Data-efficient Learning of Physics from Point Clouds
B. D. Shaffer, S. Koohy, B. Kinch, M. A. Hsieh, N. Trask
Submitted to NeurIPS 2026, Sydney, Australia
arXiv

20267 publications
Journal

Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes
V. Edwards, T. C. Silva, and M. A. Hsieh
Advanced Intelligent Systems, 2026
DOIarXiv

Conference

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs
B. D. Shaffer, S. Koohy, B. Kinch, M. A. Hsieh, N. Trask
ICML 2026, Seoul, South Korea
arXivPDF

Conference

Multi-robot Multi-source Localization in Complex Flows with Physics-Preserving Environment Models
B. D. Shaffer, V. Edwards, B. Kinch, N. Trask, M. A. Hsieh
ICRA 2026, Vienna, Austria
arXivPDF

Journal

Coupled Jet Coordination and Physical Arrangement in Salp-Inspired Multi-Robot Swimming
Z. Yang, Y. Zhang, J. Li, N. Mulay, M. A. Hsieh, K. R. Sutherland, P. E. Arratia, and C. Sung
Bioinspiration & Biomimetics, 20(6), Oct 2025
DOIarXiv

202512 publications
Journal

Air-Ground Collaboration for Language-Specified Missions in Unknown Environments
F. Cladera, Z. Ravichandran, J. Hughes, V. Murali, C. Nieto-Granda, M. A. Hsieh, G. Pappas, C. J. Taylor, V. Kumar
IEEE Transactions on Field Robotics, vol. 2, pp. 626–642, 2025
DOIarXiv

Journal

Flow-Based Localization and Mapping for Multi-Robot Systems
A. Kumar, T. C. Silva, V. Edwards, and M. A. Hsieh
IEEE Robotics and Automation Letters, vol. 10, no. 4, pp. 3278–3285, Apr 2025
DOIarXiv

Journal

Spectrally Informed Learning of Fluid Flows
B. D. Shaffer, J. R. Vorenberg, and M. A. Hsieh
Chaos, 35(3), pp. 033126, Mar 2025
DOIarXiv

Conference

KoopMotion: Learning Almost Divergence Free Koopman Flow Fields for Motion Planning
A. K. Li, T. C. Silva, V. Edwards, V. Kumar, M. A. Hsieh
CoRL 2025, Seoul, Korea
arXivPDF

Conference

Flying Quadrotors in Very Close Proximity using Learning-based Model Predictive Control
K. Y. Chee, P. A. Hsieh, G. Pappas, and M. A. Hsieh
ICRA 2025, Atlanta, GA
arXivPDFVideo

Conference

EvMAPPER: High-altitude Orthomapping with Event Cameras
F. Cladera, K. Chaney, M. A. Hsieh, C. J. Taylor, and V. Kumar
ICRA 2025, Atlanta, GA
arXivPDF

202410 publications
Journal

EnKode: Active Learning of Unknown Flows with Koopman Operators
A. K. Li, T. C. Silva, and M. A. Hsieh
IEEE Robotics and Automation Letters, vol. 9, no. 12, pp. 11282–11289, Dec 2024
DOIarXiv

Journal

Inferring Bifurcation Diagrams with Transformers
L. Zhornyak, M. A. Hsieh, and E. Forgoston
Chaos, 34, 051102, 2024
DOIarXiv

Conference

Enabling Large-scale Heterogeneous Collaboration with Opportunistic Communications
F. Cladera, Z. Ravichandran, I. D. Miller, M. A. Hsieh, C. J. Taylor, and V. Kumar
ICRA 2024, Yokohama, Japan
arXivPDF

Conference

Uncertainty Quantification and Robustification of Model-based Controllers using Conformal Prediction
K. Y. Chee, T. C. Silva, M. A. Hsieh, and G. J. Pappas
L4DC 2024, Oxford, UK
arXivPDF

202312 publications
Journal

Heterogeneous robot teams for modeling and prediction of multiscale environmental processes
T. Salam and M. A. Hsieh
Autonomous Robots, Apr 2023
DOIarXiv

Conference

Enhancing Sample Efficiency and Uncertainty Compensation in Learning-based MPC for Aerial Robots
K. Y. Chee, T. C. Silva, M. A. Hsieh, and G. J. Pappas
IROS 2023, Detroit, MI
DOIarXiv

Conference

Energy-efficient Team Orienteering Problem in the Presence of Time-Varying Ocean Currents
A. Mansfield, D. G. Macharet, and M. A. Hsieh
IROS 2023, Detroit, MI
DOIarXiv

202216 publications
Journal

KNODE-MPC: A Knowledge-Based Data-Driven Predictive Control Framework for Aerial Robots
K. Y. Chee, T. Z. Jiahao and M. A. Hsieh
IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 2819–2826, Apr 2022
DOIarXivVideoCode

Conference

NODEO: A Neural ODE Based Optimization Framework for Deformable Image Registration
Y. Wu, T. Z. Jiahao, J. Wang, P. A. Yushkevich, M. A. Hsieh, J. C. Gee
CVPR 2022, New Orleans, LA
DOIarXivCode

Conference

Learning to Swarm with Knowledge-Based Neural Ordinary Differential Equations
T. Z. Jiahao, L. Pan, and M. A. Hsieh
ICRA 2022, Philadelphia, PA
DOIarXivVideo

Conference

Flow-Based Control of Marine Robots in Gyre-Like Environments
G. Knizhnik, P. Li, X. Yu, and M. A. Hsieh
ICRA 2022, Philadelphia, PA
DOIarXiv

Show 105 earlier publications (2007–2021) ↓

Books & book chapters
Edited volumes, contributed chapters, and white papers.
Book

Adaptive Sampling and Energy Efficient Navigation in Time-Varying Flows
T. Salam, D. Kularatne, E. Forgoston, and M. A. Hsieh
in Autonomous Underwater Vehicles: Design and Practice, Institution of Engineering and Technology, 2020
DOIPDF

Edited

The 14th International Symposium on Experimental Robotics
M. A. Hsieh, O. Khatib, and V. Kumar (Eds.)
Springer Tracts in Advanced Robotics, Vol 109, Springer 2015
DOI

Edited

The 11th International Symposium on Distributed Autonomous Robotic Systems
M. A. Hsieh and G. Chirikjian (Eds.)
Springer Tracts in Advanced Robotics, Vol 104, Springer 2014
DOI

Chapter

Robustness in the Presence of Task Differentiation in Robot Ensembles
M. A. Hsieh and T. W. Mather
in Redundancy in Robot Manipulators and Multi-Robot Systems, Springer 2013
DOIPDF

Chapter

Ant-Inspired Allocation: Top-Down Controller Design for Distributing a Robot Swarm among Multiple Tasks
S. Berman, A. Halasz, and M. A. Hsieh
in Bio-inspired Computing and Communication Networks, CRC Press 2010
PDF

Patents
Intellectual property arising from ScalAR Lab research.
Patent

Collaborative Robot Manifold Tracker
M. A. Hsieh, E. Forgoston, and I. B. Schwartz
US Patent Application No. 101,738 and 101,738-US3
USPTO

Gratefully supported by

Current support
NSF
ONR
ARL

Past support
NRL
GoMRI