Papers
25
Total Citations
472
H-Index
11
About
Karthik Dantu is a leading researcher in robotics and networked systems, whose work bridges the gap between distributed robotics, sensor networks, and robot learning. His pioneering contributions include the development of Robomote, a mobile sensor network platform that demonstrated how to integrate mobility into resource-constrained sensor nodes—a foundational concept cited over 216 times. Dantu has made significant advances in multi-robot coordination, particularly in task allocation for swarms of micro-aerial vehicles, and in enabling robust communication in lossy network environments. His research on detecting and tracking level sets of scalar fields using robotic sensor networks has provided practical algorithms for environmental monitoring. More recently, Dantu has focused on integrating physics-based optimization with deep learning through PyPose, a library for robot learning that addresses generalization challenges in dynamic environments. His work on adaptive fovea for scanning depth sensors and persistence reasoning in visual SLAM has advanced perception in robotics. With over 388 citations across his most influential papers, Dantu's research continues to shape the fields of mobile sensor networks, swarm robotics, and robot learning.
Research Focus
Key Achievements
Top Papers
- 1Robomote: enabling mobility in sensor networks216 citations · 2005
- 2PyPose: A Library for Robot Learning with Physics-based Optimization35 citations · 2023
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- 5Relative bearing estimation from commodity radios20 citations · 2009
- 6Adaptive fovea for scanning depth sensors16 citations · 2020
- 7Autonomous biconnected networks of mobile robots14 citations · 2008
- 8Learning Robot Swarm Tactics over Complex Adversarial Environments14 citations · 2021
- 9Decentralized Task Allocation in Lossy Networks: A Simulation Study13 citations · 2019
- 10Practical Persistence Reasoning in Visual SLAM13 citations · 2020