Our research spans across robotic problems from estimation through planning to control with a focus on efficent distributed algorithms for multi-robot platforms.

1. R. N. Haksar, J. Lorenzetti, and M. Schwager, “Scalable Filtering of Large Graph-Coupled Hidden Markov Models,” in 2019 IEEE 58th Conference on Decision and Control (CDC), Dec. 2019, pp. 1307–1314. [pdf] [bibtex]
2. E. Cristofalo, E. Montijano, and M. Schwager, “Consensus-based Distributed 3D Pose Estimation with Noisy Relative Measurements,” in 2019 IEEE 58th Conference on Decision and Control (CDC), Dec. 2019, pp. 2646–2653. [pdf] [bibtex]
3. H. Nishimura and M. Schwager, “Active Motion-Based Communication for Robots with Monocular Vision,” in 2018 IEEE International Conference on Robotics and Automation (ICRA), May 2018, pp. 2948–2955. [pdf] [bibtex]
4. P. M. Dames, M. Schwager, D. Rus, and V. Kumar, “Active Magnetic Anomaly Detection Using Multiple Micro Aerial Vehicles,” IEEE Robotics and Automation Letters, vol. 1, no. 1, pp. 153–160, Jan. 2016. [pdf] [bibtex]
5. X. Lan and M. Schwager, “Rapidly Exploring Random Cycles: Persistent Estimation of Spatiotemporal Fields With Multiple Sensing Robots,” IEEE Transactions on Robotics, vol. 32, no. 5, pp. 1230–1244, Oct. 2016. [pdf] [bibtex]
6. G. Habibi, J. McLurkin, Z. Wang, Z. Kingston, and M. Schwager, “Pipelined Consensus for Global State Estimation in Multi-Agent Systems,” in 2015 International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2015, pp. 1315–1323. [pdf] [bibtex]

1. K. Leahy, E. Cristofalo, C.-I. Vasile, A. Jones, E. Montijano, M. Schwager, and C. Belta, “Control in belief space with temporal logic specifications using vision-based localization,” The International Journal of Robotics Research, vol. 38, no. 6, pp. 702–722, May 2019. [pdf] [bibtex]
2. T. Halsted and M. Schwager, “Distributed multi-robot localization from acoustic pulses using Euclidean distance geometry,” in 2017 International Symposium on Multi-Robot and Multi-Agent Systems (MRS), Dec. 2017, pp. 104–111. [pdf] [bibtex]
3. E. Cristofalo, K. Leahy, C.-I. Vasile, E. Montijano, M. Schwager, and C. Belta, “Localization of a Ground Robot by Aerial Robots for GPS-Deprived Control with Temporal Logic Constraints,” in 2016 International Symposium on Experimental Robotics, 2017, vol. 1, pp. 525–537. [pdf] [bibtex]

1. A. Caccavale and M. Schwager, “Trust But Verify: A Distributed Algorithm for Multi-Robot Wireframe Exploration and Mapping,” in 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019, pp. 3294–3301. [pdf] [bibtex]
2. A. Caccavale and M. Schwager, “Wireframe Mapping for Resource-Constrained Robots,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct. 2018, pp. 1–9. [pdf] [bibtex]
3. A. Caccavale and M. Schwager, “A distributed algorithm for mapping the graphical structure of complex environments with a swarm of robots,” in 2017 IEEE International Conference on Robotics and Automation (ICRA), May 2017, pp. 1459–1466. [pdf] [bibtex]

1. Ding, Huanyu, E. Cristofalo, J. Wang, D. Castanon, E. Montijano, V. Saligrama, and M. Schwager, “A multi-resolution approach for discovery and 3-D modeling of archaeological sites using satellite imagery and a UAV-borne camera,” in 2016 American Control Conference (ACC), Jul. 2016, pp. 1359–1365. [pdf] [bibtex]

1. O. Shorinwa, J. Yu, T. Halsted, A. Koufos, and M. Schwager, “Distributed Multi-Target Tracking for Autonomous Vehicle Fleets,” in 2020 IEEE International Conference on Robotics and Automation (ICRA), May 2020, pp. 3495–3501. [pdf] [bibtex]
2. K. Leahy and M. Schwager, “Always choose second best: Tracking a moving target on a graph with a noisy binary sensor,” in 2016 European Control Conference (ECC), Jun. 2016, pp. 1715–1721. [pdf] [bibtex]
3. P. Dames, M. Schwager, V. Kumar, and D. Rus, “A decentralized control policy for adaptive information gathering in hazardous environments,” in 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), Dec. 2012, pp. 2807–2813. [pdf] [bibtex]