Papers
4
Total Citations
61
H-Index
4
About
M. V. Dileep is a leading researcher in robotics, with a primary focus on trajectory planning, inverse kinematics, and multi-robot coordination. His work addresses critical challenges in industrial automation and autonomous systems. A key contribution is his development of an optimal time-jerk trajectory planning method for 6-axis welding robots using the Teaching-Learning-Based Optimization (TLBO) algorithm, which significantly improves welding precision and efficiency. This paper has garnered 26 citations, reflecting its impact on manufacturing robotics. Dileep has also advanced soft computing techniques for predicting inverse kinematics in industrial robot arms, a fundamental problem in robot control, cited 16 times. More recently, he has pioneered robust, online multi-robot exploration and coverage path planning, introducing a Manhattan Voronoi partitioning method for workspace allocation in the presence of obstacles. His 2023 and 2024 papers on this topic, with 13 and 6 citations respectively, are shaping the future of autonomous multi-robot systems. Through his innovative algorithms, Dileep is making industrial and collaborative robots more precise, efficient, and autonomous.
Research Focus
Key Achievements
Top Papers
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