Pranabesh Sarkar

Papers

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About

Pranabesh Sarkar is a robotics researcher specializing in autonomous navigation, path planning, and obstacle avoidance systems. His work focuses on developing intelligent algorithms that enable robots and rovers to operate independently in complex, unstructured environments. Sarkar’s most influential paper, “Autonomous Rover Navigation Using GPS Based Path Planning” (2017), has garnered 16 citations and addresses the growing need for perceptive robots capable of functioning in hazardous or inaccessible terrains. In this work, he integrates GPS data with machine learning techniques to create robust navigation frameworks for autonomous rovers. His second highly cited paper, “2D mapping and vertex finding method for path planning in autonomous obstacle avoidance robotic system” (2017, 10 citations), introduces a novel method for continuous navigation that combines real-time 2D mapping with range sensor data to avoid collisions. This approach is applicable to both indoor and outdoor settings, demonstrating Sarkar’s versatility in solving real-world robotics challenges. His contributions are particularly relevant as AI and robotics increasingly intersect, pushing the boundaries of autonomous systems in search-and-rescue, exploration, and industrial automation. Sarkar’s work provides foundational techniques for researchers and engineers developing next-generation autonomous vehicles and mobile robots.