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About

Z. J. Diggins is a researcher specializing in radiation effects on robotic systems, sensor degradation, and adaptive control strategies for nuclear remediation environments. Their work addresses one of the most pressing challenges in deploying autonomous robots in hazardous nuclear settings: understanding and mitigating the impact of ionizing radiation on critical sensing and control components. Diggins' most influential contribution, "Range-Finding Sensor Degradation in Gamma Radiation Environments" (2014, 21 citations), rigorously characterizes how gamma radiation compromises commercial rangefinders, establishing a foundational framework for evaluating sensor reliability under radiation exposure. Building on this, their 2016 study on MEMS accelerometers (14 citations) goes further by pairing degradation analysis with adaptive control strategies, demonstrating practical pathways for maintaining robot functionality even as hardware deteriorates. A particularly innovative thread in Diggins' research is the application of Bayesian inference to model radiation effects at both the component and system levels, enabling probabilistic predictions of overall system health — work that bridges hardware physics with intelligent systems design. Collectively, their publications have contributed meaningfully to the emerging field of radiation-hardened robotics, offering both diagnostic tools and mitigation strategies that could prove vital in future nuclear disaster response scenarios.