Human tactile acuity relies on the microstructured morphology of the fingertips, which enables sensitive detection of fine surface features during object manipulation. While triboelectric-based self-powered object recognition has gained much attention, conventional triboelectric materials are typically non-biodegradable, contributing to persistent electronic waste. This work focuses on fabricating biodegradable triboelectric interfaces for intelligent robotic texture perception and sustainable energy harvesting. Three biodegradable polymers, polylactide (PLA), poly(epsilon-caprolactone) (PCL), and poly(lactide-co-trimethylene carbonate) (PTMC), were evaluated as negative triboelectric layers against an aluminum electrode to form a single-electrode triboelectric nanogenerator (TENG). The PCL/Al TENG achieved a superior electrical output of 118 V and 772 nA, with a peak power of 24.5 & micro;W at 200 M Omega, primarily due to its higher surface roughness enhancing charge transfer. The powering of the low-power electronics and charging of the capacitors using the TENG was demonstrated. In addition, the platform was integrated into a robotic gripper for real-time texture recognition. Combined with a convolutional neural network (CNN), the system achieved 96.9% classification accuracy across eight distinct textures. This sustainable platform reduces environmental impact by using degradable materials while maintaining the mechanical robustness required for advanced robotic sensing.