Sathiyamoorthi Arthanari
Papers
2
Total Citations
26
H-Index
2
About
Sathiyamoorthi Arthanari is a rising researcher at the intersection of computer vision and swarm robotics, whose work is shaping the future of autonomous multi-agent systems. His primary research areas include visual object tracking, deep learning-based correlation filters, and distributed control for nonholonomic mobile robot swarms. Arthanari’s most influential contribution is his work on context-aware environmental residual correlation filters, which leverages deep convolutional features to significantly enhance the robustness and accuracy of visual tracking—a critical capability for applications in intelligent surveillance, autonomous navigation, and swarm robot coordination. This work has already garnered 23 citations since 2024, underscoring its immediate impact. More recently, he has tackled the complex challenge of tracking control in swarms of nonholonomic wheeled mobile robots, proposing a cascade-based distributed estimator framework using a leader–follower approach. By integrating sliding-mode control with kinematic law design, his 2025 paper offers a scalable solution for coordinating multiple robots in dynamic environments. Arthanari’s dual focus on perception and control makes his research uniquely positioned to advance real-world autonomous systems, from drone swarms to warehouse logistics.
Research Focus
Key Achievements
Top Papers
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