Decomposition-based multi-objective evolutionary algorithm for vehicle routing problem with stochastic demands SB Gee, WA Arokiasami, J Jiang, KC Tan Soft Computing 20 (9), 3443-3453, 2016 | 38 | 2016 |
Interoperable multi-agent framework for unmanned aerial/ground vehicles: towards robot autonomy WA Arokiasami, P Vadakkepat, KC Tan, D Srinivasan Complex & Intelligent Systems 2, 45-59, 2016 | 28 | 2016 |
A multi-agent approach for service restoration with distributed generation A Sharma, WA Arokiasami, D Srinivasan 2013 IEEE Innovative smart grid technologies-Asia (ISGT Asia), 1-6, 2013 | 10 | 2013 |
Fuzzy logic controllers for navigation and control of AR. Drone using microsoft kinect P Vadakkepat, TC Chong, WA Arokiasami, X Weinan 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 856-863, 2016 | 7 | 2016 |
Solving vehicle routing problem with stochastic demand using multi-objective evolutionary algorithm J Jiang, SB Gee, WA Arokiasami, KC Tan 2014 International Conference on Soft Computing and Machine Intelligence …, 2014 | 7 | 2014 |
Real-time Path-generation and Path-following using an Interoperable Multi-Agent Framework WA Arokiasami, P Vadakkepat, KC Tan, D Srinivasan Unmanned Systems 6 (4), 231-250, 0 | 7* | |
Vector directed path generation and tracking for autonomous unmanned aerial/ground vehicles WA Arokiasami, P Vadakkepať, KC Tan, D Srinivasan 2016 IEEE Congress on Evolutionary Computation (CEC), 1375-1381, 2016 | 5 | 2016 |
Impact of the length of optical flow vectors in estimating time-to-contact an obstacle WA Arokiasami, TK Chen, D Srinivasan, P Vadakkepat Proceedings of the 18th Asia Pacific Symposium on Intelligent and …, 2015 | 4 | 2015 |
Designing a multi-agent framework for unmanned aerial/ground vehicles WA Arokiasami PQDT-Global, 2016 | 2 | 2016 |
Wingbeat generation for a 15 dof flexible-wing aerial vehicle using cosine wave functions WA Arokiasami, P Vadakkepat, AA Mamun Unmanned Systems 5 (02), 115-127, 2017 | 1 | 2017 |