Papers
8
Total Citations
155
H-Index
5
About
Mayur V. Andulkar is a robotics researcher whose work centers on robot programming, trajectory generation, and human-robot interaction, with particular emphasis on industrial automation applications. He has made significant contributions to the field of automated spray painting, developing novel offline trajectory generation approaches that allow robots to navigate complex, free-form surfaces with precision. His most influential work — "Novel integrated offline trajectory generation approach for robot assisted spray painting operation" (2015, 69 citations) — alongside his incremental trajectory generation framework (54 citations) established him as a key voice in automating surface-finishing tasks using CAD-model-driven programming techniques. Beyond spray painting, Andulkar has explored intuitive robot programming through human motion imitation, leveraging Kinect-based sensing systems and arm kinematics to enable natural, demonstration-based robot control — work that bridges the gap between human dexterity and industrial robotics. His research also extends to mobile manufacturing systems, flexible assembly operations, and self-adaptive robotic frameworks for semi-structured environments. With over 150 cumulative citations, his portfolio reflects a consistent drive to reduce manufacturing waste, improve automation flexibility, and make robot programming more accessible and efficient — contributions of direct relevance to researchers working at the intersection of industrial robotics and intelligent manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Incremental approach for trajectory generation of spray painting robot54 citations · 2015
- 3Kinematics-based approach for robot programming via human arm motion10 citations · 2016
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- 7Self adaptive system for flexible robot assembly operation5 citations · 2016
- 8