Papers
6
Total Citations
56
H-Index
4
About
Pramit Dutta is a robotics researcher whose work spans autonomous navigation, deep learning for perception, and remote handling systems for extreme environments. His key contributions lie in three interconnected areas: path planning for mobile robots, transformer-based scene understanding for autonomous driving, and robotic maintenance for nuclear fusion reactors. In his highly cited 2017 paper on complete coverage path planning, Dutta developed algorithms enabling robots to efficiently map and traverse known 2D environments—a foundational capability for autonomous mobile platforms. More recently, his 2022 work on ViT-BEVSeg introduced a hierarchical transformer network for monocular bird’s-eye-view segmentation, a critical task for self-driving vehicles that demands robust near-field perception from a single camera. Beyond terrestrial robotics, Dutta has made notable contributions to fusion energy research, including the development of a hyper-redundant robot for tokamak inspection and an OROCOS-based real-time controller for remote maintenance systems. His work on deep Q-learning for robotic arm navigation in tokamak environments further demonstrates his commitment to deploying intelligent, autonomous systems in hazardous, human-inaccessible settings. With over 50 citations across his most-cited papers, Dutta’s research bridges fundamental robotics algorithms with high-impact applications in energy and transportation.
Research Focus
Key Achievements
Top Papers
- 1Complete coverage path planning algorithm for known 2d environment21 citations · 2017
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- 4A Hyper-Redundant Robot Development for Tokamak Inspection5 citations · 2017
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- 6Deep Q-Learning for Navigation of Robotic Arm for Tokamak Inspection3 citations · 2018