Pablo R. Bodmann
Papers
2
Total Citations
8
H-Index
2
About
Pablo R. Bodmann is a researcher at the forefront of reliable autonomous systems, specializing in the intersection of deep reinforcement learning, computer vision, and fault-tolerant computing for safety-critical robotics. His work addresses a pressing challenge: ensuring the dependability of AI-powered robots operating in extreme environments, from planetary exploration to human-interactive tasks. Bodmann’s major contributions include pioneering reliability assessments of deep reinforcement learning policies on EdgeAI accelerators, such as Google’s Coral Edge TPU, where he demonstrated how neutron-induced faults can compromise autonomous decision-making. His 2024 paper on this topic, with 6 citations, provides critical insights for deploying robots in radiation-prone settings. Additionally, his evaluation of Vision Transformers for space robotics applications (2 citations) advances the understanding of how modern perception models perform under resource constraints and environmental stressors. By quantifying the vulnerabilities of deep learning models on edge devices, Bodmann is shaping the design of more robust AI systems for autonomous navigation and human-robot interaction. His work is essential reading for engineers and researchers developing resilient AI for space, defense, and industrial robotics.
Research Focus
Key Achievements
Top Papers
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