Sajjad Haider
Papers
14
Total Citations
101
H-Index
6
About
Sajjad Haider is a leading researcher in multi-robot systems, specializing in task allocation, coordinated strategy, and evolutionary optimization. His work addresses the fundamental challenge of enabling teams of robots to work together efficiently, with a particular focus on dynamic environments like robot soccer. Haider’s most impactful contribution is the development of the Rostam framework, a flexible system for diverse multi-robot task allocation scenarios that allows robots to multi-task, significantly reducing operational time and energy. This work, published in 2021, has already garnered 12 citations. His research on teaching coordinated strategies to soccer robots via imitation learning (22 citations) and using evolutionary algorithms for strategy optimization (7 citations) has been foundational in the field. Haider has also explored bipedal locomotion, evolving dynamic walks using Partial Fourier Series, and has published a comprehensive survey on nature-inspired optimization algorithms for cooperative strategies. With over 90 total citations, his work is essential reading for anyone interested in the practical application of evolutionary computation and machine learning to multi-agent coordination and robotics.
Research Focus
Key Achievements
Top Papers
- 1Teaching coordinated strategies to soccer robots via imitation22 citations · 2012
- 2An Evolutionary Traveling Salesman Approach for Multi-Robot Task Allocation16 citations · 2017
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- 7On learning coordination among soccer agents6 citations · 2012
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- 9On evolving a dynamic bipedal walk using Partial Fourier Series4 citations · 2012
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