Papers
11
Total Citations
314
H-Index
5
About
Pushyami Kaveti is a robotics researcher whose work spans autonomous navigation, simultaneous localization and mapping (SLAM), and human-robot interaction. He gained early prominence as a contributor to Team IHMC's efforts in the DARPA Robotics Challenge Trials, a landmark project developing robots capable of disaster response, which remains his most cited work with 242 citations and reflects his roots in real-world, high-stakes robotics deployment. His research has since evolved to tackle some of the most persistent challenges in robot perception, including robust SLAM in dynamic and multi-floor indoor environments, multi-camera visual SLAM frameworks, and optimal sensor arrangement strategies — the latter addressed through his OASIS framework. Kaveti has also explored innovative approaches to handling dynamic objects using light field imaging, improving the reliability of visual SLAM in cluttered, real-world settings. Beyond navigation, his work extends to teleoperation systems for the Avatar XPRIZE competition and applied machine learning for underwater fish detection. Through publications spanning competitive robotics, sensor design, and autonomous systems, Kaveti has established himself as a versatile and practically minded researcher pushing the boundaries of robot perception and embodied intelligence.
Research Focus
Key Achievements
Top Papers
- 1Team IHMC's Lessons Learned from the DARPA Robotics Challenge Trials242 citations · 2015
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- 5OASIS: Optimal Arrangements for Sensing in SLAM6 citations · 2024
- 6ROS Rescue: Fault Tolerance System for Robot Operating System5 citations · 2020
- 7Towards Automated Fish Detection Using Convolutional Neural Networks4 citations · 2018
- 8Towards Robust VSLAM in Dynamic Environments: A Light Field Approach3 citations · 2021
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