Tapas Badal

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About

Tapas Badal is a researcher specializing in autonomous robotics and embedded intelligence, with a particular focus on real-time navigation systems for indoor environments. His most-cited work, "Corridor segmentation for automatic robot navigation in indoor environment using edge devices" (2020), has garnered 25 citations, demonstrating its influence in the field. This paper addresses a critical challenge in robotics: enabling efficient, low-latency navigation without reliance on cloud computing. By developing algorithms that run directly on edge devices, Badal’s research bridges the gap between computational efficiency and practical deployment, making autonomous navigation more accessible for resource-constrained robots. His contributions are particularly valuable for applications in smart buildings, warehouses, and assistive robotics, where real-time decision-making is essential. Badal’s work underscores the importance of optimizing computer vision and segmentation techniques for embedded systems, paving the way for more responsive and autonomous indoor robots. His research continues to inspire advancements in edge AI and mobile robotics, offering a blueprint for integrating intelligence directly into robotic hardware.