Tusar Kanti Mishra

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About

Tusar Kanti Mishra is a researcher specializing in mobile robotics, computer vision, and intelligent navigation systems. His work focuses on developing cost-effective solutions for autonomous robots, particularly in indoor environments. Mishra’s major contributions include a QR code-based indoor navigation system for an attender robot, which addresses key challenges in localization and navigation using affordable technology. This paper has garnered 13 citations, reflecting its practical relevance in robotics research. Additionally, he has advanced activity recognition through a PSO-based combined kernel learning framework for first-person video analysis, earning 11 citations. This work demonstrates his expertise in machine learning and video processing, offering novel approaches to understanding human actions from an egocentric perspective. Mishra’s research bridges the gap between theoretical algorithms and real-world applications, making him a notable figure in the fields of autonomous systems and intelligent robotics. His achievements highlight a commitment to innovation in cost-effective, scalable technologies for mobile robots and video-based activity recognition.