Combining biological components and machines could be a novel solution for sensing and actuation, considering the strong functional capability of living organisms. But it seemed to be ignored that plants and mycology systems also respond to environmental changes, with special advantages on the low requirement for living environment, long lifetime, and low cost. In this study, we evaluated and developed the methodology and system to hybrid robots with King Oyster. Standard culturing and noise mitigated data acquisition system was first designed for long-term recordings. Fungal spontaneous signals were then analyzed. Both frequency domain filters and time-domain data processing methods were applied to extract convincing features from the relatively stochastic signal. Obvious electrical behavior alternation was observed with heat and UV added as an external stimulus to prove the sensing ability. After understanding the signal, we stepped to build a soft robot design and then integrate fungi-inspired artifact PWM signal. With the embedded signal, we achieved about 0.12 BL/min crawling speed.