Publications

2017

  1. D. Devaurs, D. A. Antunes, M. Papanastasiou, M. Moll, D. Ricklin, J. D. Lambris, and L. E. Kavraki, “Coarse-Grained Conformational Sampling of Protein Structure Improves the Fit to Experimental Hydrogen-Exchange Data,” Frontiers in Molecular Biosciences, vol. 4, no. 13, Mar. 2017.
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  2. A. Novinskaya, D. Devaurs, M. Moll, and L. E. Kavraki, “Defining Low-Dimensional Projections to Guide Protein Conformational Sampling,” Journal of Computational Biology, vol. 24, no. 1, pp. 79–89, Jan. 2017.
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  3. W. Baker, Z. Kingston, M. Moll, J. Badger, and L. Kavraki, “Robonaut 2 and You: Specifying and Executing Complex Operations,” in IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Austin, TX, 2017.
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2016

  1. S. Butler, M. Moll, and L. E. Kavraki, “A General Algorithm for Time-Optimal Trajectory Generation Subject to Minimum and Maximum Constraints,” in Workshop on the Algorithmic Foundations of Robotics, 2016.
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  2. J. D. Hernández, M. Moll, E. Vidal Garcia, M. Carreras, and L. E. Kavraki, “Planning Feasible and Safe Paths Online for Autonomous Underwater Vehicles in Unknown Environments,” in IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, 2016, pp. 1313–1320.
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  3. M. Moll, P. W. Finn, and L. E. Kavraki, “Structure-Guided Selection of Specificity Determining Positions in the Human Kinome,” BMC Genomics, Aug. 2016.
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  4. S. M. Kim, M. I. Peña, M. Moll, G. Giannakopoulos, G. N. Bennett, and L. E. Kavraki, “An Evaluation of Different Clustering Methods and Distance Measures Used for Grouping Metabolic Pathways,” in Eighth International Conference on Bioinformatics and Computational Biology (BICoB), 2016.
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  5. L. E. Kavraki and M. Moll, “Special Issue on the 2014 ‘Robotics: Science & Systems’ Conference (Guest Editorial),” Intl. J. of Robotics Research, vol. 35, no. 1–3, pp. 3–4, Mar. 2016.
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  6. D. Devaurs, M. Papanastasiou, D. Antunes, J. Abella, M. Moll, D. Ricklin, J. Lambris, and L. E. Kavraki, “Native State of Complement Protein C3d Analyzed via Hydrogen Exchange and Conformational Sampling,” in Intl. Conf. on Intelligent Biology and Medicine (ICIBM), 2016.
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2015

  1. A. Novinskaya, D. Devaurs, M. Moll, and L. E. Kavraki, “Improving Protein Conformational Sampling by Using Guiding Projections,” in IEEE Intl. Conf. on Bioinformatics and Biomedicine Workshops (BIBMW), 2015, pp. 1272–1279.
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  2. M. Moll, P. W. Finn, and L. E. Kavraki, “Structure-Guided Selection of Specificity Determining Positions in the Human Kinome,” in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2015, pp. 21–28.
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  3. M. Moll, I. A. Şucan, and L. E. Kavraki, “Benchmarking Motion Planning Algorithms: An Extensible Infrastructure for Analysis and Visualization,” IEEE Robotics & Automation Magazine (Special Issue on Replicable and Measurable Robotics Research), vol. 22, no. 3, pp. 96–102, Sep. 2015.
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  4. D. K. Grady, M. Moll, and L. E. Kavraki, “Extending the Applicability of POMDP Solutions to Robotic Tasks,” IEEE Trans. on Robotics, vol. 31, no. 4, pp. 948–961, Aug. 2015.
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  5. C. Voss, M. Moll, and L. E. Kavraki, “A Heuristic Approach to Finding Diverse Short Paths,” in IEEE Intl. Conf. on Robotics and Automation, 2015, pp. 4173–4179.
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  6. D. Coleman, I. A. Şucan, M. Moll, K. Okada, and N. Correll, “Experience-Based Planning with Sparse Roadmap Spanners,” in IEEE Intl. Conf. on Robotics and Automation, 2015, pp. 900–905.
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  7. R. Luna, M. Lahijanian, M. Moll, and L. E. Kavraki, “Asymptotically Optimal Stochastic Motion Planning with Temporal Goals,” in Algorithmic Foundations of Robotics XI, vol. 107, H. L. Akin, N. M. Amato, V. Isler, and A. F. van der Stappen, Eds. Springer Verlag, 2015, pp. 335–352.
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2014

  1. R. Luna, M. Lahijanian, M. Moll, and L. E. Kavraki, “Optimal and Efficient Stochastic Motion Planning in Partially-Known Environments,” in 28th AAAI Conference on Artificial Intelligence (AAAI-14), Québec City, Canada, 2014, pp. 2549–2555.
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  2. S. Nedunuri, S. Prabhu, M. Moll, S. Chaudhuri, and L. E. Kavraki, “SMT-Based Synthesis of Integrated Task and Motion Plans from Plan Outlines,” in IEEE Intl. Conf. on Robotics and Automation, 2014, pp. 655–662.
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  3. Z. Wang, Z. Wang, M. Moll, P.-S. Huang, D. Grady, N. Nasrabadi, T. Huang, L. Kavraki, and M. Hasegawa-Johnson, “Active Planning, Sensing and Recognition Using a Resource-Constrained Discriminant POMDP,” in IEEE/ISPRS Workshop on Multi-Sensor Fusion for Outdoor Dynamic Scene Understanding at CVPR, 2014.
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  4. R. Luna, M. Lahijanian, M. Moll, and L. E. Kavraki, “Fast Stochastic Motion Planning with Optimality Guarantees using Local Policy Reconfiguration,” in IEEE Intl. Conf. on Robotics and Automation, 2014, pp. 3013–3019.
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2013

  1. D. K. Grady, M. Moll, and L. E. Kavraki, “Combining a POMDP Abstraction with Replanning to Solve Complex, Position-Dependent Sensing Tasks,” in AAAI Fall Symposium, Arlington, VA, 2013.
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  2. J. Chyan, M. Moll, and L. E. Kavraki, “Improving the Prediction of Kinase Binding Affinity Using Homology Models,” in Computational Structural Bioinformatics Workshop at the ACM Conf. on Bioinf., Comp. Bio. and Biomedical Informatics, Washington, DC, 2013, pp. 741–748.
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  3. B. Gipson, M. Moll, and L. E. Kavraki, “SIMS: A hybrid method for rapid conformational analysis,” PLOS ONE, vol. 8, no. 7, p. e68826, Jul. 2013.
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  4. D. H. Bryant, M. Moll, P. W. Finn, and L. E. Kavraki, “Combinatorial clustering of residue position subsets predicts inhibitor affinity across the human kinome,” PLOS Computational Biology, vol. 9, no. 6, p. e1003087, Jun. 2013.
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  5. D. K. Grady, M. Moll, and L. E. Kavraki, “Automated Model Approximation for Robotic Navigation with POMDPs,” in IEEE Intl. Conf. on Robotics and Automation, 2013, pp. 78–84.
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  6. M. Moll, J. Bordeaux, and L. E. Kavraki, “Software for Project-Based Learning of Robot Motion Planning,” Computer Science Education, Special Issue on Robotics in CS Education, vol. 23, no. 4, pp. 332–348, 2013.
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  7. R. Luna, I. A. Şucan, M. Moll, and L. E. Kavraki, “Anytime Solution Optimization for Sampling-Based Motion Planning,” in IEEE Intl. Conf. on Robotics and Automation, 2013, pp. 5053–5059.
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  8. B. Gipson, M. Moll, and L. E. Kavraki, “Resolution Independent Density Estimation for Motion Planning in High-Dimensional Spaces,” in IEEE Intl. Conf. on Robotics and Automation, 2013, pp. 2429–2435.
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2012

  1. I. A. Şucan, M. Moll, and L. E. Kavraki, “The Open Motion Planning Library,” IEEE Robotics & Automation Magazine, vol. 19, no. 4, pp. 72–82, Dec. 2012. http://ompl.kavrakilab.org
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  2. K. E. Bekris, D. K. Grady, M. Moll, and L. E. Kavraki, “Safe Distributed Motion Coordination for Second-Order Systems with Different Planning Cycles,” Intl. J. of Robotics Research, vol. 31, no. 2, pp. 129–149, Feb. 2012.
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  3. D. K. Grady, M. Moll, C. Hegde, A. C. Sankaranarayanan, R. G. Baraniuk, and L. E. Kavraki, “Multi-Objective Sensor-Based Replanning for a Car-Like Robot,” in IEEE Intl. Symp. on Safety, Security, and Rescue Robotics, 2012.
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  4. D. K. Grady, M. Moll, C. Hegde, A. C. Sankaranarayanan, R. G. Baraniuk, and L. E. Kavraki, “Multi-Robot Target Verification with Reachability Constraints,” in IEEE Intl. Symp. on Safety, Security, and Rescue Robotics, 2012.
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2011

  1. M. Moll, D. H. Bryant, and L. E. Kavraki, “The LabelHash Server and Tools for Substructure-Based Functional Annotation,” Bioinformatics, vol. 27, no. 15, pp. 2161–2162, Jun. 2011.
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  2. M. Moll, I. A. Şucan, J. Bordeaux, and L. E. Kavraki, “Teaching Motion Planning Concepts to Undergraduate Students,” in IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), 2011.
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  3. D. K. Grady, M. Moll, C. Hegde, A. C. Sankaranarayanan, R. G. Baraniuk, and L. E. Kavraki, “Look Before You Leap: Predictive Sensing and Opportunistic Navigation,” in Workshop on Progress and Open Problems in Motion Planning at the IEEE/RSJ Conf. on Intelligent Robots and Systems, 2011.
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2010

  1. M. Moll, D. H. Bryant, and L. E. Kavraki, “The LabelHash Algorithm for Substructure Matching,” BMC Bioinformatics, vol. 11, no. 555, Nov. 2010.
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  2. D. H. Bryant, M. Moll, B. Y. Chen, V. Y. Fofanov, and L. E. Kavraki, “Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction,” BMC Bioinformatics, vol. 11, no. 242, May 2010.
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  3. M. Moll, J. Bordeaux, and L. E. Kavraki, “Teaching Robot Motion Planning,” ASEE Computers in Education Journal (Special Issue on Novel Approaches to Robotics Education), vol. 20, no. 3, pp. 50–59, 2010.
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  4. N. Haspel, M. Moll, M. L. Baker, W. Chiu, and L. E. Kavraki, “Tracing Conformational Changes in Proteins,” BMC Structural Biology, vol. 10, no. Suppl. 1, p. S1, 2010.
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2009

  1. N. Haspel, M. Moll, M. L. Baker, W. Chiu, and L. E. Kavraki, “Tracing Conformational Changes in Proteins,” in IEEE Intl. Conf. on Bioinformatics and Biomedicine Workshops (BIBMW), Washington, DC, 2009, pp. 120–127.
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2008

  1. M. Moll and D. Rus, “Special Issue on Self-Reconfiguring Modular Robots (Guest Editorial),” Intl. J. of Robotics Research, vol. 27, no. 3/4, pp. 277–278, Mar. 2008.
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  2. V. Y. Fofanov, B. Y. Chen, D. H. Bryant, M. Moll, O. Lichtarge, L. E. Kavraki, and M. Kimmel, “A statistical model to correct systematic bias introduced by algorithmic thresholds in protein structural comparison algorithms,” in IEEE Intl. Conf. on Bioinformatics and Biomedicine Workshops (BIBMW), 2008, pp. 1–8.
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  3. M. Moll and L. E. Kavraki, “Matching of Structural Motifs Using Hashing on Residue Labels and Geometric Filtering for Protein Function Prediction,” in The Seventh Annual International Conference on Computational Systems Bioinformatics (CSB2008), 2008, pp. 157–168.
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  4. M. Moll and L. E. Kavraki, “LabelHash: A Flexible and Extensible Method for Matching Structural Motifs,” in Automated Function Prediction / BioSapiens Meeting (AFP-BioSapiens), Toronto, Canada, 2008. Available from Nature Precedings
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2007

  1. M. Moll, D. Schwarz, and L. E. Kavraki, “Roadmap Methods for Protein Folding,” in Protein Structure Prediction: Methods and Protocols, Second., M. Zaki and C. Bystroff, Eds. Humana Press, 2007.
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  2. M. Yim, W.-M. Shen, B. Salemi, D. Rus, M. Moll, H. Lipson, and E. Klavins, “Modular Self-reconfigurable Robot Systems: Challenges and Opportunities for the Future,” IEEE Robotics & Automation Magazine, vol. 14, no. 1, pp. 43–52, Mar. 2007.
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  3. W.-M. Shen, B. Salemi, M. Moll, C. H. Chiu, J. Everist, F. Hou, N. Ranasinghe, and M. Rubenstein, “Multifunctional Behaviors of Reconfigurable SuperBot Modules,” in Proc. 2007 IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, 2007. Video
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  4. B. Y. Chen, D. H. Bryant, J. H. Bylund, A. E. Cruess, D. M. Kristensen, V. Y. Fofanov, M. Moll, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Representations of Structural Motifs for Protein Function Prediction,” in 15th Annual Intl. Conf. on Intelligent Systems for Molecular Biology (ISMB) 6th European Conf. on Comp. Bio. (ECCB), Vienna, Austria, 2007.
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  5. B. Y. Chen, D. H. Bryant, V. Y. Fofanov, D. M. Kristensen, M. Moll, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Geometry-inspired Optimization Methods for Structural Motifs for Protein Function Prediction,” in Automated Function Prediction Meeting (AFP), Vienna, Austria, 2007.
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2006

  1. B. Salemi, M. Moll, and W.-M. Shen, “SUPERBOT: A Deployable, Multi-Functional, and Modular Self-Reconfigurable Robotic System,” in Proc. 2006 IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, Beijing, China, 2006, pp. 3636–3641.
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  2. M. Moll, P. Will, M. Krivokon, and W.-M. Shen, “Distributed Control of the Center of Mass of a Modular Robot,” in Proc. 2006 IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, Beijing, China, 2006, pp. 4710–4715.
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  3. M. Moll and L. E. Kavraki, “Path Planning for Deformable Linear Objects,” IEEE Trans. on Robotics, vol. 22, no. 4, pp. 625–636, Aug. 2006.
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  4. P. Das, M. Moll, H. Stamati, L. E. Kavraki, and C. Clementi, “Low-dimensional, free-energy landscapes of protein-folding reactions by nonlinear dimensionality reduction,” Proc. Natl. Acad. of Science USA, vol. 103, no. 26, pp. 9885–9890, Jun. 2006.
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2005

  1. M. Moll and L. E. Kavraki, “Path Planning for Variable Resolution Minimal-Energy Curves of Constant Length,” in Proc. 2005 IEEE Intl. Conf. on Robotics and Automation, 2005, pp. 2142–2147.
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2004

  1. M. Moll and M. A. Erdmann, “Reconstructing the Shape and Motion of Unknown Objects with Active Tactile Sensors,” in Algorithmic Foundations of Robotics V, J.-D. Boissonnat, J. Burdick, K. Goldberg, and S. Hutchinson, Eds. Springer Verlag, 2004, pp. 293–310.
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  2. M. Moll and L. E. Kavraki, “Path Planning for Minimal Energy Curves of Constant Length,” in Proc. 2004 IEEE Intl. Conf. on Robotics and Automation, 2004, pp. 2826–2831.
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  3. M. Moll, D. Schwarz, A. Heath, and L. E. Kavraki, “On Flexible Docking Using Expansive Search,” Rice University, Houston, TX, 04-443, 2004.
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2002

  1. M. Moll, “Shape Reconstruction Using Active Tactile Sensors,” PhD thesis, Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, 2002.
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  2. M. Moll and M. A. Erdmann, “Manipulation of Pose Distributions,” Intl. J. of Robotics Research, vol. 21, no. 3, pp. 277–292, Mar. 2002.
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  3. M. Moll, K. Goldberg, M. A. Erdmann, and R. Fearing, “Aligning Parts for Micro Assemblies,” Assembly Automation, vol. 22, no. 1, pp. 46–54, Feb. 2002.
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  4. M. Moll, K. Goldberg, M. A. Erdmann, and R. Fearing, “Orienting Micro-Scale Parts with Squeeze and Roll Primitives,” in Proc. 2002 IEEE Intl. Conf. on Robotics and Automation, 2002, pp. 1931–1936.
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  5. M. Moll and M. A. Erdmann, “Dynamic Shape Reconstruction Using Tactile Sensors,” in Proc. 2002 IEEE Intl. Conf. on Robotics and Automation, 2002, pp. 1636–1641.
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2001

  1. M. Moll and M. A. Erdmann, “Reconstructing Shape from Motion Using Tactile Sensors,” in Proc. 2001 IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, Maui, HI, 2001, pp. 691–700.
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  2. M. Moll and M. A. Erdmann, “Manipulation of Pose Distributions,” in Algorithmic and Computational Robotics: New Directions, B. R. Donald, K. M. Lynch, and D. Rus, Eds. A. K. Peters, 2001, pp. 127–141.
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  3. M. Moll and M. A. Erdmann, “Shape Reconstruction in a Planar Dynamic Environment,” Dept. of Computer Science, Carnegie Mellon University, CMU-CS-01-107, 2001.
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2000

  1. M. Moll and M. A. Erdmann, “Uncertainty Reduction Using Dynamics,” in Proc. 2000 IEEE Intl. Conf. on Robotics and Automation, San Francisco, California, 2000, pp. 3673–3680.
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1997

  1. M. Moll and R. Miikkulainen, “Convergence-Zone Episodic Memory: Analysis and Simulations,” Neural Networks, vol. 10, no. 6, pp. 1017–1036, 1997.
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1996

  1. M. Moll, “Mapping Science: Methods and Tools for the Automatic Creation of Semantic Maps of Large Corpora,” Centre for Science and Technology Studies (CWTS), Leiden, the Netherlands, Report CWTS 96-06, Aug. 1996. Research report to the Netherlands Organization for Scientific Research (NWO), Foundation for Economic and Socio-Cultural Sciences (ESR)
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  2. H. ter Doest, M. Moll, R. Bos, S. Van de Burgt, and A. Nijholt, “Language Engineering in Dialogue Systems,” Department of Computer Science, University of Twente, Memoranda Informatica 96-2, Jan. 1996.
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  3. H. ter Doest, M. Moll, R. Bos, S. Van de Burgt, and A. Nijholt, “Language Engineering in Dialogue Systems,” in Computers in Engineering Symposium, Houston, TX, 1996, pp. 68–79.
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1995

  1. M. Moll, “Head-corner Parsing Using Typed Feature Structures,” Master's thesis, Department of Computer Science, University of Twente, 1995.
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  2. R. op den Akker, H. ter Doest, M. Moll, and A. Nijholt, “Parsing in Dialogue Systems using Typed Feature Structures,” in Proceedings of the International Workshop on Parsing Technologies, Prague/Karlovy Vary, Czech Republic, 1995.
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  3. R. op den Akker, H. ter Doest, M. Moll, and A. Nijholt, “Parsing in Dialogue Systems using Typed Feature Structures,” Department of Computer Science, University of Twente, Memoranda Informatica 95-25, 1995.
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1994

  1. M. Moll, R. Miikkulainen, and J. Abbey, “The Capacity of Convergence-Zone Episodic Memory,” in Proc. 12th Natl. Conf. on Artificial Intelligence (AAAI-94), Cambridge, MA, 1994, pp. 68–73.
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