Amith Manoharan
Research Fellow
Institute of Technology
University of Tartu
Tartu, 50090
Estonia.
Amith Manoharan
Research Fellow
Institute of Technology
University of Tartu
Tartu, 50090
Estonia.
Visiting Researcher
Estonian Aviation Academy
Tartu, 61707
Estonia.
Amith is currently a Research Fellow at the Institute of Technology, University of Tartu, Estonia and a Visiting Researcher at the Estonian Aviation Academy. He obtained Ph. D. from Indraprastha Institute of Information Technology Delhi (IIITD) in 2023. He completed M. Tech with specialisation in Guidance, Navigation and Control from College of Engineering Trivandrum, kerala, India in 2017. He received B. Tech degree in Electrical and Electronics Engineering with honours from Government College of Engineering Kannur, Kerala, India in 2014. He was a visiting scholar with the Brigham Young University, Provo, USA from 2019-20. He was a project student at Vikram Sarabhai Space Centre (VSSC), a major research centre of Indian Space Research Organisation (ISRO) for one year (2016-17). His research interests are cooperative control of multi-agent systems, guidance and control of surface, underwater, and aerospace vehicles using optimal control techniques ( MPC, LQR, ...) and AI techniques (RL, NN, ...).
E. M. Andrejev, A. Manoharan, K. -E. Unt and A. K. Singh, "π-MPPI: A Projection-Based Model Predictive Path Integral Scheme for Smooth Optimal Control of Fixed-Wing Aerial Vehicles," in IEEE Robotics and Automation Letters, vol. 10, no. 6, pp. 6496-6503, June 2025. [PDF]
A. Manoharan, R. Sharma and S. Baliyarasimhuni, "Multi-AAV Cooperative Path Planning Using Nonlinear Model Predictive Control With Localization Constraints," in IEEE Transactions on Intelligent Transportation Systems, 2024. [PDF]
A. Manoharan and P. B. Sujit, "Nonlinear Model Predictive Control Framework for Cooperative Three-Agent Target Defense Game", Journal of Intelligent & Robotic Systems, 108 (2), 21, 2023. [PDF]
A. Manoharan and P. B. Sujit, "NMPC-Based Cooperative Strategy to Lure Two Attackers Into Collision by Two Targets", IEEE Control Systems Letters, 7, 496-501, 2022. [PDF]
A. Manoharan, A. Sharma, H. Belsare, K. Pal, K. M. Krishna and A. K. Singh, "Bi-level Trajectory Optimization on Uneven Terrains with Differentiable Wheel-Terrain Interaction Model, "IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Abu Dhabi, 2024. [PDF]
A. Manoharan, P. Thakur, and A. K. Singh, "Multi-agent Target Defense Game with Learned Defender to Attacker Assignment", International Conference on Unmanned Aircraft Systems, Warsaw, 2023. [PDF]
D. Soni, A. Manoharan, P. Tyagi, and P. B. Sujit, "Learning-based NMPC Framework for Car Racing Cinematography Using Fixed-Wing UAV", International Conference on Unmanned Aircraft Systems, Dubrovnik, 2022. [PDF]
A. Manoharan, R. Sharma, and P.B. Sujit, “Nonlinear Model Predictive Control to Aid Cooperative Localization”, International Conference on Unmanned Aircraft Systems, Atlanta, 2019. [PDF]
M. Singh, A. Manoharan, A. Ratnoo, and P.B. Sujit, “Three Dimensional UAV Path Following Using SDRE Guidance”, International Conference on Unmanned Aircraft Systems, Atlanta, 2019. [PDF]
A. Manoharan, M. Singh, A. Alessandretti, J.G. Manathara, S.C. Prusty, N. Mohanty, I.S. Kumar, A. Sahoo, and P.B. Sujit, “NMPC Based Approach for Cooperative Target Defence”, American Control Conference, Philadelphia, 2019. [PDF]
Y. Kumar, A. Manoharan and P.B. Sujit, “Right of Way Rules based Collision Avoidance Approach Using Model Predictive Control”, Indian Control Conference, 2019. [PDF]
A. Manoharan, “Three-agent Pursuit-evasion Problem: A Review”, in Proc. of the 42nd National Systems Conference, Thiruvananthapuram, 2018. [PDF]
A. Manoharan, M. Selvaraaj, and P. S. Shenil, “Geostationary Orbit Payload Improvement using Lunar Gravity Assist”, in Proc. of the 18th National Conference on Technological Trends, Thiruvananthapuram, 2017. [PDF]
A. Manoharan, "Strategies for cooperative UAVs using model predictive control." Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2021. [PDF]
SekMo (Cross-Sectoral Mobility Measure) grant scheme by Estonian Research Council, co-financed by the European Union’s European Regional Development Fund (ERDF) – 50,000 EUR
Teaching Assistant award from IIITD for Winter ’18 (Optimal Control Systems) and Monsoon ’18 (Control Theory)