Chiranjib Guha Majumder
Papers
2
Total Citations
6
H-Index
2
About
Chiranjib Guha Majumder is a robotics researcher whose work focuses on intelligent motion planning and autonomous navigation for mobile robots and multi-robot systems. His research addresses the fundamental challenge of enabling robots to operate safely and efficiently in dynamic, unknown environments. A key contribution is his work on dynamic obstacle avoidance, where he developed a novel prediction-based approach for multi-robot path planning. This method anticipates the linear motion of obstacles that change direction at regular intervals, allowing robot teams to proactively avoid collisions rather than simply reacting to them. His research also extends to real-time, sensor-driven navigation, where he has applied fuzzy logic to extract and utilize infrared sensory data. This approach allows a mobile agent to learn reactive strategies through offline training, enabling it to interact with and navigate through unfamiliar spaces without a pre-built map. While his most cited works, published in 2012, have garnered foundational citations, they represent early, principled steps toward more adaptive and predictive robotic systems—a critical area for the future of autonomous logistics, exploration, and collaborative robotics.
Research Focus
Key Achievements
Top Papers
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- 2