Journal Papers

A. M. Wells, N. T. Dantam, A. Shrivastava, and L. E. Kavraki, “Learning Feasibility for Task and Motion Planning in Tabletop Environments,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1255–1262, Apr. 2019. http://dx.doi.org/10.1109/LRA.2019.2894861

Conference Papers

C. Disselkoen, A. Eline, S. He, K. Headley, M. Hicks, K. Hietala, J. Kastner, A. Mamat, M. McCutchen, N. Rungta, E. Torlak, B. Shaah, and A. M. Wells. “How We Built Cedar: A Verification-Guided Approach” in Foundations of Software Engineering (FSE), 2024.

J. W. Cutler, C. Disselkoen, A. Eline, S. He, K. Headley, M. Hicks, K. Hietala, E. Ioannidis, J. Kastner, A. Mamat, D. McAdams, M. McCutchen, N. Rungta, E. Torlak, and A. M. Wells. “Cedar: A New Language for Expressive, Fast, Safe, and Analyzable Authorization” in Object-oriented Programming, Systems, Languages, and Applications (OOPSLA), 2024.

K. Muvvala, A. M. Wells, M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “Stochastic Games for Interactive Manipulation Domains” in IEEE International Conference on Robotics and Automation, 2024. To Appear.

S. Bansal, Y. Li, L. M. Tabajara, M. Y. Vardi, and A. M. Wells, “Model Checking Strategies from Synthesis Over Finite Traces” in Automated Technology for Verification and Analysis (ATVA) 2023. (Best paper award)

T. Pan, A. M. Wells, R. Shome and L. E. Kavraki, “Failure Is an Option: Task and Motion Planning with Failing Executions,” in 2022 International Conference on Robotics and Automation (ICRA), 2022, pp. 1947–1953.

S. Bansal, L. E. Kavraki, M. Y. Vardi and A. M. Wells, “Synthesis from Satisfycing and Temporal Goals,” in Proceedings of the AAAI Conference on Artifical Intelligence, 2022, vol. 36, no. 9, pp. 9679–9686.

T. Pan, A. M. Wells, R. Shome, and L. E. Kavraki, “A General Task and Motion Planning Framework For Multiple Manipulators,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021. http://dx.doi.org/10.1109/iros51168.2021.9636119

A. M. Wells, Z. Kingston, M. Lahijanian, L. E. Kavraki and M. Y. Vardi, “Finite Horizon Synthesis for Probabilistic Manipulation Domains,” in IEEE Intl. Conf. on Robotics and Automation, Xi’an China, 2021. http://dx.doi.org/10.1109/icra48506.2021.9561297

A. M. Wells, M. Lahijanian, L. E. Kavraki and M. Y. Vardi, “LTLf Synthesis on Probabilistic Systems,” Electronic Proceedings in Theoretical Computer Science, vol. 326, pp. 166–181, Sep. 2020. http://dx.doi.org/10.4204/eptcs.326.11

T. Pan, C. K. Verginis, A. M. Wells, D.V. Dimarogonas and L. E. Kavraki, “Augmenting Control Policies with Motion Planning for Robust and Safe Multi-robot Navigation,” in IEEE Intl. Conf. on Intelligent Robots and Systems, 2020, pp. 6975-6981, http://dx.doi.org/10.1109/IROS45743.2020.9341153

Z. Kingston, A. M. Wells, M. Moll, and L. E. Kavraki, “Informing Multi-Modal Planning with Synergistic Discrete Leads,” in IEEE Intl. Conf. on Robotics and Automation, Paris, France, 2020, pp. 3199-3205, http://dx.doi.org/10.1109/ICRA40945.2020.9197545

K. He, A. M. Wells, L. E. Kavraki, and M. Y. Vardi, “Efficient Symbolic Reactive Synthesis for Finite-Horizon Tasks,” in IEEE Intl. Conf. on Robotics and Automation, 2019, pp. 8993–8999. http://dx.doi.org/10.1109/ICRA.2019.8794170 (Best paper award in Cognitive Robotics)

A. Wells and E. Plaku. “Adaptive Sampling Based Motion Planning for Mobile Robots with Differential Constraints.” Springer LNCS Towards Autonomous Robotic Systems, vol. 9287, pp. 283–295 http://link.springer.com/chapter/10.1007%2F978-3-319-22416-9_32 (Best student paper award)

Workshop Papers

M. O’Neil, A. Wells and X. Sun. “Towards a novel and efficient packet identifier design for SDN” Proceedings of the third workshop on Hot topics in software defined networking (HotSDN), 2014, pp. 223-224. http://dl.acm.org/citation.cfm?id=2620728.2620775

Patents

Authorization Policy Analysis. Publication No. US-20240179188-A1. Published 2024-05-30. Under review, may not be granted.

Authorization Policy Evaluation. Publication No. US-20240179181-A1. Published 2024-05-30. Under review, may not be granted.