Jashaswimalya Acharjee

National Institute of Technology Agartala

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About

Jashaswimalya Acharjee is a researcher at the intersection of robotics, geospatial data analysis, and autonomous navigation. Their work focuses on leveraging graph-theoretic approaches to interpret LIDAR data, enabling efficient point-to-point floor exploration for indoor Automated Guided Vehicles (AGVs). Acharjee’s key contribution lies in developing novel analytical frameworks that transform raw LIDAR point clouds into navigable graph structures, allowing AGVs to map and traverse complex indoor environments with improved accuracy and reduced computational overhead. This approach addresses critical challenges in warehouse automation, healthcare logistics, and smart building management. Their most cited paper, "Avenues of Graph Theoretic Approach of Analysing the LIDAR Data for Point-To-Point Floor Exploration by Indoor AGV" (2023), has garnered 2 citations, reflecting early recognition in a rapidly evolving field. Acharjee’s work bridges theoretical graph theory with practical robotics applications, offering scalable solutions for real-world autonomous systems. Their research holds promise for advancing indoor navigation technologies, particularly in environments where GPS is unavailable, and contributes to the broader goal of creating more intelligent, self-navigating machines.