Rajasekar Mohan
Papers
2
Total Citations
8
H-Index
2
About
Rajasekar Mohan is a robotics researcher focused on making autonomous systems more accessible and practical for everyday environments. His work centers on two critical challenges in mobile and humanoid robotics: stable locomotion and affordable spatial awareness. In his 2020 study on humanoid gait generation, Mohan developed a geometric analysis approach to solve inverse kinematics, enabling small-sized humanoid robots to produce stable walking patterns—a foundational step toward deploying humanoid platforms in domestic automation. This work has garnered 4 citations for its novel kinematic methodology. Complementing this, his 2019 research tackled the high cost of autonomous navigation by demonstrating Simultaneous Localization and Mapping (SLAM) using only low-cost ultrasonic sensors, offering a viable alternative to expensive LIDAR and RGB-D cameras. This approach, also cited 4 times, shows how household robots can perceive and map their surroundings without breaking the budget. Together, Mohan’s contributions advance the goal of cost-effective, capable robots that can operate safely and autonomously in human-centered spaces, bridging the gap between research prototypes and real-world home applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2