Haresh P. Patolia

Anand Agricultural University, Sri Padmavati Mahila Visvavidyalayam

Papers

Total Citations

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About

Haresh P. Patolia is a robotics researcher specializing in the kinematics and motion control of parallel manipulators, with a particular focus on the Delta robot. His work addresses the fundamental challenge of solving forward kinematics (FK) for parallel configurations—a problem that is inherently more complex than inverse kinematics. Patolia’s major contributions include the development of a novel hybrid neural network that optimizes a Multilayer Perceptron (MLP) using a Genetic Algorithm, achieving accurate FK solutions for Delta robots. This work, published in 2021, has garnered 6 citations, reflecting its relevance in the field of robotic control. In a complementary study, he advanced model-based motion simulation by designing and simulating a Delta parallel robot within Simulink’s SimScape environment, enabling realistic motion planning and validation. This research, also from 2021, has received 5 citations. Patolia’s innovative integration of machine learning with robotic kinematics offers practical pathways for improving the precision and efficiency of parallel robots, making his work valuable for students and researchers in robotics and automation.