Pranav Atreya

The University of Texas at Austin

Papers

3

Total Citations

58

H-Index

3

About

Pranav Atreya is a rising star in robotics, whose work is pushing the boundaries of autonomous navigation and manipulation. His research centers on two critical challenges: enabling high-speed, accurate off-road navigation by learning complex vehicle-terrain dynamics, and achieving zero-shot robotic manipulation in unstructured environments. Atreya's major contributions include the development of VI-IKD, a visual-inertial inverse kinodynamics framework that allows ground vehicles to navigate at high speeds across dramatically varying terrains (31 citations). He further advanced this field with a method combining learned forward kinodynamics with non-linear least squares optimization for precise high-speed control (17 citations). In manipulation, Atreya introduced SuSIE, a pioneering approach that leverages pretrained image-editing diffusion models to enable robots to manipulate novel objects without any task-specific training data (10 citations). This work represents a significant leap toward generalist robots capable of reasoning about unseen scenarios. Atreya's innovative fusion of learning-based kinodynamics with diffusion models marks him as a key contributor to the next generation of agile, adaptable autonomous systems.

Research Focus

Key Achievements

3
H-Index
3
Papers
58
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics
31 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: The University of Texas at Austin

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago