Papers
2
Total Citations
85
H-Index
2
About
Poonam Savsani is a researcher whose work sits at the intersection of robotics and advanced computational optimization. Her primary research focus is on trajectory planning for robotic arms, a critical problem in automation where efficiency and precision are paramount. Savsani’s major contribution lies in systematically applying and comparing a suite of modern metaheuristic algorithms to solve this complex, multi-objective challenge. In her highly cited 2014 paper (54 citations), she conducted a landmark comparative study of seven different metaheuristics—including the Artificial Bee Colony (ABC) algorithm and biogeography-based optimization—for optimizing the path of a 3R robotic arm. This work provided a crucial benchmark for the field. She further advanced the state of the art by pioneering the application of the Teaching Learning Based Optimization (TLBO) algorithm to robotic trajectory planning in a 2013 study (31 citations), demonstrating its effectiveness alongside ABC. By rigorously evaluating these nature-inspired algorithms, Savsani has helped establish a clear framework for selecting the most efficient optimization strategy for robotic motion, directly impacting the design of faster, more energy-efficient automated systems.
Research Focus
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Top Papers
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