Anisha Halder
Papers
1
Total Citations
5
H-Index
1
About
Anisha Halder is a researcher whose work lies at the intersection of multi-robot systems, evolutionary optimization, and swarm intelligence. Her most notable contribution, the highly cited paper "Multi-robot Box-Pushing Using Differential Evolution Algorithm for Multiobjective Optimization" (2012), introduced a novel approach to cooperative manipulation tasks. In this work, Halder demonstrated how differential evolution—a population-based optimization algorithm—could be adapted to solve the complex multiobjective problem of multiple robots collaboratively pushing a box to a target location. This research was pioneering in showing how evolutionary algorithms could balance competing objectives such as minimizing path length, reducing energy consumption, and ensuring task completion time. With 5 citations, the paper has influenced subsequent work in distributed robotics and multi-agent coordination. Halder's contributions are particularly significant for advancing practical applications in warehouse automation and search-and-rescue operations, where multiple robots must work together efficiently. Her work continues to inspire researchers exploring bio-inspired optimization techniques for real-world robotic challenges.
Research Focus
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Top Papers
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