Shotabdi Roy
Papers
1
Total Citations
8
H-Index
1
About
Shotabdi Roy is a researcher at the forefront of integrating computer vision and artificial intelligence into cost-effective robotic systems. Her most cited work, "A computer vision and artificial intelligence based cost-effective object sensing robot" (2019), exemplifies her commitment to making advanced sensing technology accessible. In this study, she developed an affordable robot capable of real-time object detection and navigation, leveraging AI algorithms to interpret visual data without expensive hardware. This contribution addresses a critical gap in robotics—balancing performance with economic feasibility—and has garnered 8 citations, reflecting its relevance in both academic and applied contexts. Roy’s research primarily focuses on embedded AI, low-cost sensor fusion, and autonomous navigation, aiming to democratize robotics for education, small-scale industry, and developing regions. Her work stands out for its practical impact, offering a blueprint for scalable, intelligent systems that bridge the gap between high-end research and real-world deployment. Through her innovative approach, Roy is shaping a future where intelligent robots are not just powerful, but also widely accessible.
Research Focus
Key Achievements
Top Papers
- 1