Papers
3
Total Citations
19
H-Index
3
About
Rohit Chandra is a robotics researcher specializing in dynamic modeling, human-robot collaboration, and skill learning for industrial applications. His work bridges theoretical modeling with practical robotic systems, particularly in challenging environments like urban search and rescue (USAR) and manufacturing. Chandra’s most cited paper, “Modelling and Dynamic Identification of 3 DOF Quanser Helicopter” (2013, 10 citations), develops a nonlinear dynamic model using robotics notations, treating the helicopter as a tree-structured rigid-link robot—a foundational contribution to aerial robotics control. His 2016 paper on a “Knowledge-Based Framework for Human-Robots Collaborative Context Awareness in USAR Missions” (5 citations) advances situational awareness for robot teams, enabling intuitive human-robot decision-making in disaster response. Most recently, his 2023 work on “Dual quaternion based dynamic movement primitives to learn industrial tasks using teleoperation” (4 citations) introduces a novel method for imitating complex human tasks, such as deformable object manipulation, using dual quaternion representations. This approach enhances robot learning from demonstration, with direct implications for automating difficult industrial processes. With a cumulative 19+ citations across these works, Chandra’s research demonstrates a clear trajectory from foundational modeling to applied human-robot interaction and skill transfer, making him a notable contributor to modern robotics.
Research Focus
Key Achievements
Top Papers
- 1Modelling and Dynamic Identification of 3 DOF Quanser Helicopter10 citations · 2013
- 2
- 3