Applied Algorithms

Our research group has collaborated with other groups to apply task and motion planning to several multidisciplinary research projects. We have used our algorithms in real-world applications to plan for the motion of Autonomous Ground Vehicles (AGV), robotic manipulators, and insect-scale robots that can jump and glide. We have applied our algorithms to enable efficient and real-time multi-robot task allocation to use robots to automate manufacturing workstations. We have applied our algorithms outside of traditional robotics, including computer aided design (CAD), AR/VR and even problems in computational biology, including modeling protein folding and pharmaceutical drug design. Motion planning methods can also be used for automating the design of complex systems such as for designing the routing of wires in a car.

Publications

• Gressmann, F. , Chen, A. , Xie, L.H. , Amato, N.M. , & Rauchwerger, L. (2025). Position: It Is Time We Test Neural Computation In Vitro. Proceedings of the 42nd International Conference on Machine Learning (ICML 2025). View publication
• Chen, T. , Huang, Z. , Motes, J. , Geng, J. , Ta, Q.M. , Dinkel, H. , Abdul-Rashid, H. , Myers, J. , Mun, Y. , Lin, W. , Huang, Y. , Liu, S. , Morales, M. , Amato, N.M. , Driggs-Campbell, K. , & Bretl, T. (2022). Insights from an Industrial Collaborative Assembly Project: Lessons in Research and Collaboration. ICRA 2022 WORKSHOP ON COLLABORATIVE ROBOTS AND THE WORK OF THE FUTURE. arXiv
• Solis, I. , Motes, J. , Sandström, R. , & Amato, N.M. (2021). Representation-Optimal Multi-Robot Motion Planning using Conflict-Based Search. IEEE Robotics and Automation Letters. https://doi.org/https://doi.org/10.1109/LRA.2021.3068910
• Uwacu, D. , Ren, A. , Thomas, S. , & Amato, N.M. (2020). Using Guided Motion Planning to Study Binding Site Accessibility. Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics , 10. https://doi.org/10.1145/3388440.3414707
• Ekenna, C. , Thomas, S. , & Amato, N.M. (2016). Adaptive Local Learning in Sampling Based Motion Planning for Protein Folding. BMC Syst Biol, Special Issue from the 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) , 10(49) , 165--179. https://doi.org/10.1186/s12918-016-0297-9
• Yeh, H.(. , Lindsey, A. , Wu, C. , Thomas, S. , & Amato, A.N.M. (2015). Decoy Database Improvement for Protein Folding. Journal of Computational Biology , 22(9) , 823-836. https://doi.org/10.1089/cmb.2015.0116
• Thomas, S. , Tapia, L. , Ekenna, C. , Yeh, H.(. , & Amato, N.M. (2013). Rigidity Analysis for Protein Motion and Folding Core Identification. Association for the Advancement of Artificial Intelligence (AAAI) Workshop , WS-13-06 , 38-43. View publication
• Nath, S. , Thomas, S. , Ekenna, C. , & Amato, N.M. (2012). A Multi-Directional Rapidly Exploring Random Graph (mRRG) for Protein Folding. Proc. ACM Conference on Bioinformatics, Computational Biology and Biomedicine (BCB) , 44-51. https://doi.org/10.1145/2382936.2382942
• Tapia, L. , Thomas, S. , & Amato, N.M. (2010). A Motion Planning Approach to Studying Molecular Motions. Communications in Information and Systems , 10 , 52-68. https://doi.org/10.4310/cis.2010.v10.n1.a4
• Tang, X. , Thomas, S. , Tapia, L. , & Amato, N.M. (2007). Tools for Simulating and Analyzing RNA Folding Kinetics. In. Proc. International Conference on Research in Computational Molecular Biology , 268--282. https://doi.org/10.1007/978-3-540-71681-5_19
• Bayazit, O.B. , Xie, D. , & Amato, N.M. (2005). Iterative Relaxation of Constraints: A Framework for Improving Automated Motion Planning. In Proc. IEEE Int. Conf. Intel. Rob. Syst. (IROS) , 3433-3440. https://doi.org/10.1109/IROS.2005.1545045
• Amato, N.M. , Dill, K.A. , & Song, G. (2004). Using Motion Planning to Map Protein Folding Landscapes and Analyze Folding Kinetics of Known Native Structures. Journal of Computational Biology , 10(3-4) , 239-255. https://doi.org/10.1089/10665270360688002
• Tang, X. , Kirkpatrick, B. , Thomas, S. , Song, G. , & Amato, N.M. (2004). Using Motion Planning to Study RNA Folding Kinetics. In Proc. Int. Conf. Comput. Molecular Biology (RECOMB) , 252–261. https://doi.org/10.1145/974614.974648
• Song, G. , Thomas, S. , Dill, K.A. , Scholtz, J.M. , & Amato, N.M. (2003). A Path Planning-based Study of Protein Folding With a Case Study of Hairpin Formation in Protein G and L. In Proc. Pac. Symp. of Biocomputing (PSB) , 8 , 240-251. View publication