Seth Karten

Rutgers, The State University of New Jersey

Papers

Total Citations

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About

Seth Karten is a robotics researcher specializing in autonomous systems, with a focus on underwater and vehicular navigation. His work bridges the gap between perception, planning, and adaptive control, addressing key challenges in real-time environmental sensing and motion planning. Karten’s most cited paper, “SLAM-based Underwater Adaptive Sampling Using Autonomous Vehicles” (2018, 14 citations), introduces a novel strategy for autonomous underwater vehicles (AUVs) to efficiently map and sample 3D water bodies in near real time, leveraging simultaneous localization and mapping (SLAM) to optimize sensing coverage. This contribution is critical for oceanography and environmental monitoring. In “Improving Kinodynamic Planners for Vehicular Navigation with Learned Goal-Reaching Controllers” (2021, 6 citations), Karten proposes a learning framework that enhances sampling-based kinodynamic planners by using reinforcement learning to identify promising control actions, improving path quality and computational efficiency for dynamic vehicular systems. His research demonstrates a strong interdisciplinary approach, combining SLAM, adaptive sampling, and machine learning to push the boundaries of autonomous navigation in complex, unstructured environments. Karten’s work is particularly impactful for students and researchers interested in field robotics, marine autonomy, and intelligent motion planning.