Papers
2
Total Citations
4
H-Index
2
About
Rakesh Kumar Sanodiya is a researcher advancing the frontiers of autonomous robotics and human-machine interaction. His work centers on two pivotal challenges: enabling robust robotic navigation and improving the classification of biological signals for assistive technologies. In robotics, Sanodiya addresses the critical limitations of path-following algorithms, which often fail under varying environments and unknown parameters. His 2024 paper, "Generalized Visual Path Following on Jetbot Using Normalization with Reinforcement Learning," introduces a practical, adaptive solution that leverages reinforcement learning to enhance the Jetbot’s autonomous navigation, earning 2 citations for its innovative approach to a persistent problem. Simultaneously, Sanodiya tackles the complexities of human-machine interaction through his work on surface Electromyography (sEMG). In "EMGTTL: Transformers-Based Transfer Learning for Classification of ADL using Raw Surface EMG Signals," also from 2024, he proposes a novel transformer-based transfer learning framework that eliminates the need for time-consuming feature extraction in classifying Activities of Daily Living. This work, also with 2 citations, promises to streamline the development of more intuitive prosthetics and rehabilitation devices. Sanodiya’s research is characterized by its practical focus on overcoming real-world constraints, making his contributions directly relevant to the next generation of autonomous systems and assistive technologies.
Research Focus
Key Achievements
Top Papers
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- 2