Abhishek Majumder

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About

Abhishek Majumder is a researcher in robotics and optimization, with a focus on multi-robot systems and intelligent task allocation. His most-cited work, "Teaching–Learning-Based Optimization Algorithm for Path Planning and Task Allocation in Multi-robot Plant Inspection System" (2021, 24 citations), introduces a novel application of teaching–learning-based optimization to coordinate robots for efficient plant inspection. This contribution addresses critical challenges in industrial automation by enabling autonomous, collision-free navigation and balanced task distribution among multiple robots. Majumder’s research bridges computational intelligence and practical robotics, offering scalable solutions for real-world inspection tasks. His work has been recognized for its potential to improve productivity and safety in manufacturing and agricultural settings. With a growing citation impact, Majumder continues to advance the field of swarm robotics and optimization, making his research valuable for students and engineers seeking efficient, decentralized approaches to complex multi-robot coordination problems.