Jasgurpeet Singh Chohan
Papers
1
Total Citations
2
H-Index
1
About
Jasgurpreet Singh Chohan is an emerging researcher in the field of robotics and optimization, with a focus on enhancing the adaptability and performance of robotic manipulators. His work centers on the development of variable rigidity joints—a critical component for robots that must balance precision and flexibility in dynamic environments. In his most-cited paper, "Ensemble Approach for Optimizing Variable Rigidity Joints in Robotic Manipulators Using MOALO-MODA" (2023), Chohan introduces a novel hybrid optimization framework that combines Multi-Objective Ant Lion Optimizer (MOALO) and Multi-Objective Dragonfly Algorithm (MODA). This ensemble method demonstrates significant improvements in joint stiffness and energy efficiency, offering a scalable solution for industrial and service robotics. Though early in his career, with 2 citations on this work, his contribution is notable for its innovative integration of nature-inspired algorithms to solve complex mechanical design problems. Chohan’s research holds promise for advancing soft robotics and adaptive automation, positioning him as a rising voice in the intersection of computational intelligence and mechanical engineering.
Research Focus
Key Achievements
Top Papers
- 1