Priteshkumar Gohil
Papers
1
Total Citations
7
H-Index
1
About
Priteshkumar Gohil is a robotics researcher whose work centers on sensor fusion, multimodal learning, and robotic manipulation. His most-cited paper, “Sensor Fusion and Multimodal Learning for Robotic Grasp Verification Using Neural Networks” (2022, 7 citations), addresses a critical challenge in robotics: integrating data from diverse sensors—such as vision, tactile, and force sensors—that operate at different sampling rates and dimensionalities. Gohil’s contribution lies in developing neural network architectures that jointly process these multimodal inputs, enabling robots to verify successful grasps with higher accuracy than single-modality systems. This work has direct implications for industrial automation and assistive robotics, where reliable object handling is essential. By tackling the practical difficulty of fusing asynchronous sensor streams, Gohil advances the field toward more perceptive and adaptable robotic systems. His research is particularly valuable for students and engineers seeking to bridge the gap between theoretical sensor fusion methods and real-world robotic applications. With a growing citation record, Gohil is establishing himself as a thoughtful contributor to intelligent robotic perception and control.
Research Focus
Key Achievements
Top Papers
- 1