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  • Xuefeng Zhou; Hongmin Wu; Juan Rojas; Zhihao Xu; Shuai Li
    978-981-15-6263-1
    2020
    Edition 1
    • Is the first book on robot introspection based on nonparametric Bayesian methods in a data-driven context, which can be easily integrated into various robotic systems
    • Introduces a fast, accurate, robot anomaly monitoring, diagnosis and recovery scheme for endowing robots with longer-term autonomy and a safer collaborative environment
    • Demonstrates two robots that perform three manipulation tasks: an HIRO-NX robot that performs electronic assembly, and a Baxter robot that performs a pick-and-place task and kitting experiment, providing comprehensive guidance for professional researchers and college students
    • Is an open access book

    Open Access

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