Prashant Agrawal
Papers
1
Total Citations
23
H-Index
1
About
Prashant Agrawal is a researcher at the forefront of assistive robotics and human-robot interaction, with a particular focus on leveraging machine learning and sensor technologies to improve the lives of visually impaired individuals. His most cited work, "Machine learning and Sensor-Based Multi-Robot System with Voice Recognition for Assisting the Visually Impaired" (2023, 23 citations), introduces a novel multi-robot system that integrates voice recognition and environmental sensors to provide real-time navigation assistance. This contribution addresses a critical challenge in assistive technology: enabling safe and independent mobility for visually impaired users in unfamiliar or outdoor environments. By combining multi-agent coordination with adaptive machine learning algorithms, Agrawal’s system demonstrates how intelligent robotics can bridge the gap between human needs and technological capability. His research not only advances the field of sensor-based robotics but also underscores the importance of user-centered design in developing practical, deployable solutions. With growing citation impact, Agrawal’s work is shaping the future of accessible navigation systems, offering a compelling example of how engineering innovation can directly enhance quality of life.
Research Focus
Key Achievements
Top Papers
- 1