Dharanish Kedarisetti

Papers

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About

Dharanish Kedarisetti is a robotics researcher whose work centers on robust perception and state estimation for autonomous systems, with a particular focus on Simultaneous Localization and Mapping (SLAM) in challenging indoor environments. His most cited paper, "Large-scale Indoor Mapping with Failure Detection and Recovery in SLAM" (2024, 5 citations), tackles a critical bottleneck in visual-inertial SLAM: the system's vulnerability to failure during extended deployments. Kedarisetti's key contribution lies in developing a failure detection and recovery framework that enables camera-IMU systems to autonomously identify tracking loss or drift and restore accurate localization without human intervention. This work is foundational for reliable long-term navigation in large-scale indoor spaces, such as warehouses, hospitals, or factories, where uninterrupted mapping is essential. By addressing the practical fragility of SLAM, Kedarisetti's research bridges the gap between theoretical algorithms and real-world deployment, making his findings valuable for both academic researchers and industry practitioners working on autonomous robots. His focus on robustness and recovery mechanisms marks him as a promising contributor to the next generation of resilient robotic systems.