Varun Prakash Rajamohan
Papers
2
Total Citations
3
H-Index
1
About
Varun Prakash Rajamohan is a robotics researcher specializing in cost-effective manipulation and adaptive control systems for robotic platforms. His work centers on developing practical solutions for object decluttering in domestic and industrial environments, combining deep learning with mobile manipulation. In his highly cited 2023 paper "MoMo: Mouse-Based Motion Planning for Optimized Grasping to Declutter Objects Using a Mobile Robotic Manipulator," Rajamohan introduced a novel approach that leverages YOLO-based object detection to enable efficient grasping and clearing of spaces, demonstrating how affordable hardware can achieve sophisticated robotic tasks. His 2024 work "QCASBC: An algorithm for hardware-in-the-loop simulation of 3-link RRR robotic manipulator" presents a quick convergence adaptive sliding backstepping control algorithm for precise trajectory tracking, validated through hardware-in-the-loop simulation. This contribution advances the field of nonlinear control for articulated manipulators. With growing citation impact, Rajamohan's research bridges the gap between theoretical control methods and real-world robotic applications, offering scalable solutions for automation challenges. His work is particularly relevant for students and researchers interested in accessible robotics, adaptive control, and the integration of computer vision with manipulation systems.
Research Focus
Key Achievements
Top Papers
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