Nilanjan Chakraborty

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About

Nilanjan Chakraborty is a robotics researcher whose work sits at the intersection of motion planning, human-robot collaboration, and robotic manipulation. His research focuses on developing intelligent planning strategies that enable collaborative robots — or cobots — to operate effectively and safely in dynamic human environments, with particular emphasis on reducing the complexity of human guidance required for sophisticated task execution. Among his most recognized contributions is his development of coordinate-invariant, reactive planning frameworks, most notably the Rapidly Expanding Plane-Oriented Escaping Trees (RPOET) approach, which allows robots to adapt fluidly to environmental changes without burdensome reprogramming. Building on this, his work on screw geometry-based motion planning offers an elegant mathematical framework for teaching robots complex manipulation tasks through human demonstration, significantly lowering barriers to robot programming in constrained settings. Chakraborty has also demonstrated a strong commitment to applying robotics to real-world challenges, including containerized vertical farming — a domain where spatial constraints demand highly efficient cobot deployment. His publications have collectively garnered around 30 citations within just a few years, reflecting growing community interest in his practical, geometry-informed approach to making collaborative robots more adaptable, intuitive, and broadly deployable across industrial and agricultural settings.