减轻机器人系统中传感器电离剂量失效的机器学习技术

2018 18th European Conference on Radiation and Its Effects on Components and Systems (RADECS) Pub Date : 2018-09-01 DOI:10.1109/radecs45761.2018.9328649

L. C. Adams, J. Howard, E. J. Barth, peixiong zhao, R. A. Reed, R. A. Peters, A. Witulski

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引用次数: 1

摘要

机器学习用于扩展机器人系统在TID传感器故障时的性能。该方法在机械臂上实现，以演示提交给模拟辐射效应的编码器信号的重建。

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Machine Learning Techniques for Mitigating Sensor Ionizing Dose Failures in Robotic Systems

Machine learning is used to extend performance in robotic systems suffering from TID sensor failure. The method is implemented on a robotic manipulator to demonstrate reconstruction of encoder signals submitted to simulated radiation effects.

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来源期刊

2018 18th European Conference on Radiation and Its Effects on Components and Systems (RADECS)

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