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About

S.S. Mahapatra is a researcher specializing in robotics, multi-criteria decision-making (MCDM), and intelligent computational methods for robotic systems. His work sits at the intersection of industrial automation and decision science, addressing practical challenges in robot selection and kinematic analysis that are highly relevant to modern manufacturing environments. Mahapatra's most influential contributions focus on applying advanced MCDM frameworks to the complex problem of industrial robot selection. His 2016 studies extending the PROMETHEE method (25 citations) and applying the TODIM approach (18 citations) provide structured, rigorous methodologies for evaluating robots across both objective and subjective criteria — a significant challenge given the vast variety of robotic configurations available in today's market. These works have become valuable references for engineers and decision-makers navigating automation investments. Beyond decision-making frameworks, Mahapatra has contributed to robotic kinematics through the application of Adaptive Neuro-Fuzzy Inference Systems (ANFIS), developing predictive models for solving inverse kinematics problems in redundant manipulators ranging from 2-DOF to 5-DOF configurations. These studies demonstrate his broader interest in intelligent soft-computing approaches to robot control and trajectory planning. Collectively, his research offers practical tools that bridge theoretical robotics with real-world industrial applications.