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About

Dr. Jayasree Chakraborty is a leading researcher in multi-robot coordination and swarm intelligence, whose work has fundamentally advanced the field of cooperative autonomous systems. Her primary research focuses on developing robust, optimization-driven solutions for multi-robot path planning and manipulation tasks, particularly in noisy and uncertain environments. Dr. Chakraborty’s most significant contributions include pioneering the use of parallel differential evolution algorithms for both centralized and distributed multi-robot path planning, a breakthrough that has garnered over 115 citations across her foundational papers. She also introduced a novel multi-objective optimization framework for the classical box-pushing problem, employing NSGA-II to generate Pareto-optimal solutions that allow robots to simultaneously translate and rotate objects—a key achievement in cooperative manipulation. Her work on robust path planning using particle swarm optimization further demonstrates her ability to address real-world challenges, such as sensor noise. With a total of over 140 citations from her most-cited works, Dr. Chakraborty’s research has become essential reading for students and engineers working on evolutionary robotics, swarm intelligence, and autonomous navigation, establishing her as a respected authority in cooperative multi-robot systems.