Papers
12
Total Citations
217
H-Index
6
About
Gunji Bala Murali is a leading researcher in robotic path planning, assembly sequence optimization, and trajectory planning for industrial manipulators. His work focuses on developing and hybridizing nature-inspired metaheuristic algorithms—such as the cuckoo search, bat algorithm, and teaching-learning-based optimization—to solve complex, multi-objective optimization problems in robotics and manufacturing. His most cited paper, “Optimal Path Planning of Mobile Robot Using Hybrid Cuckoo Search-Bat Algorithm” (69 citations), introduces a novel hybrid approach that significantly improves path efficiency in dynamic environments. He has also made substantial contributions to assembly sequence planning, with his 2018 paper on assembly subsets detection using TLBO (67 citations) and his 2019 work on stability graph-based assembly (37 citations) providing practical frameworks for reducing assembly time and cost in industries like aerospace and defense. Murali’s research extends to trajectory optimization for SCARA and planar manipulators, where he has applied multi-objective ant lion and modified bat algorithms. With over 200 total citations, his work bridges algorithmic innovation and real-world industrial application, offering efficient, scalable solutions for modern manufacturing challenges.
Research Focus
Key Achievements
Top Papers
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- 5Robotic Optimal Assembly Sequence Using Improved Cuckoo Search Algorithm6 citations · 2018
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- 9Robotic Assembly Sequence Generation Using Improved Fruit Fly Algorithm4 citations · 2020
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