| A decentralized formation and network connectivity tracking controller for multiple unmanned systems R Dutta, L Sun, D Pack IEEE Transactions on Control Systems Technology 26 (6), 2206-2213, 2017 | 55 | 2017 |
| Swarm intelligence algorithms for integrated optimization of piezoelectric actuator and sensor placement and feedback gains R Dutta, R Ganguli, V Mani Smart Materials and Structures 20 (10), 105018, 2011 | 49 | 2011 |
| Exploring isospectral spring–mass systems with firefly algorithm R Dutta, R Ganguli, V Mani Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2011 | 34 | 2011 |
| A cooperative formation control strategy maintaining connectivity of a multi-agent system R Dutta, L Sun, M Kothari, R Sharma, D Pack IEEE/RSJ International Conference on Intelligent Robots and Systems - IROS …, 2014 | 29 | 2014 |
| Multi-agent formation control with maintaining and controlling network connectivity R Dutta, L Sun, D Pack 2016 American Control Conference (ACC), 1036-1041, 2016 | 17 | 2016 |
| Exploring isospectral cantilever beams using electromagnetism inspired optimization technique R Dutta, R Ganguli, V Mani Swarm and Evolutionary Computation 9, 37-46, 2013 | 11 | 2013 |
| Gps-denied three dimensional leader-follower formation control using deep reinforcement learning RA Selje, A Al-Radaideh, R Dutta, L Sun AIAA SciTech 2022 forum, 2237, 2022 | 6 | 2022 |
| A decentralized learning strategy to restore connectivity during multi-agent formation control R Dutta, H Kandath, S Jayavelu, L Xiaoli, S Sundaram, D Pack Neurocomputing 520, 33-45, 2023 | 5 | 2023 |
| Rapid and accurate thin film thickness extraction via UV-Vis and machine learning SIP Tian, Z Liu, V Chellappan, YF Lim, Z Ren, F Oviedo, BH Teo, J Thapa, ... 2020 47th IEEE photovoltaic specialists conference (PVSC), 0128-0132, 2020 | 5 | 2020 |
| Capturing functional relations in fluid–structure interaction via machine learning T Soni, A Sharma, R Dutta, A Dutta, S Jayavelu, S Sarkar Royal Society open science 9 (4), 220097, 2022 | 4 | 2022 |
| Comparing data driven and physics inspired models for hopping transport in organic field effect transistors M Lakshminarayanan, R Dutta, DVM Repaka, S Jayavelu, WL Leong, ... Scientific Reports 11 (1), 23621, 2021 | 4 | 2021 |
| S-reinforce: A neuro-symbolic policy gradient approach for interpretable reinforcement learning R Dutta, Q Wang, A Singh, D Kumarjiguda, L Xiaoli, S Jayavelu arXiv preprint arXiv:2305.07367, 2023 | 3 | 2023 |
| Cooperative control of autonomous network topologies R Dutta The University of Texas at San Antonio, 2016 | 2 | 2016 |
| A Numerical Method for Constructing Isospectral Discrete Systems R Agarwal, R Dutta, R Ganguli International Journal for Computational Methods in Engineering Science and …, 2015 | 2 | 2015 |
| Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization R Dutta, SIP Tian, Z Liu, M Lakshminarayanan, S Venkataraj, Y Cheng, ... Plos one 17 (11), e0276555, 2022 | 1 | 2022 |
| Optimal Connectivity during Multi-agent Consensus Dynamics via Model Predictive Control H Kandath, R Dutta, J Senthilnath 2022 American Control Conference (ACC), 5193-5198, 2022 | 1 | 2022 |
| Robust consensus of higher-order multi-agent systems with attrition and inclusion of agents and switching topologies JV Pushpangathan, H Kandath, R Dutta, R Bardhan, J Senthilnath arXiv preprint arXiv:2202.06261, 2022 | 1 | 2022 |
| A generic formation controller and state observer for multiple unmanned systems R Dutta, C Qian, L Sun, D Pack arXiv preprint arXiv:1709.01321, 2017 | 1 | 2017 |
| Role of Iso-connectivity Topologies in Multi-agent Interactions R Dutta, D Pack arXiv preprint arXiv:1606.03641, 2016 | 1 | 2016 |
| Interpretable Policy Extraction with Neuro-Symbolic Reinforcement Learning R Dutta, Q Wang, A Singh, D Kumarjiguda, L Xiaoli, S Jayavelu ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | | 2024 |
Liang SunNew Mexico State University在 nmsu.edu 的电子邮件经过验证
