Rakesh Chandra Joshi
Papers
1
Total Citations
15
H-Index
1
About
Dr. Rakesh Chandra Joshi is a leading researcher at the intersection of robotics, artificial intelligence, and explainable machine learning. His work focuses on developing intelligent, transparent models for robotic control, with a particular emphasis on inverse kinematics and joint angle prediction for anthropomorphic systems. In his most-cited paper, "Optimized inverse kinematics modeling and joint angle prediction for six-degree-of-freedom anthropomorphic robots with Explainable AI" (2024, 15 citations), Dr. Joshi introduces a novel framework that not only achieves high accuracy in predicting complex robotic movements but also provides interpretable insights into the decision-making process—a critical step toward trustworthy human-robot collaboration. This contribution is notable for bridging the gap between high-performance optimization and model transparency, addressing a key challenge in deploying AI in safety-critical robotic applications. His work has already garnered attention for its practical implications in industrial automation and assistive robotics, establishing him as an emerging voice in the field. Dr. Joshi’s research continues to push the boundaries of how robots learn and explain their actions, promising safer and more intuitive interactions between humans and machines.
Research Focus
Key Achievements
Top Papers
- 1