摘要 : An ultra-low-power object matching processor is proposed for the autonomous micro air vehicle (MAV) navigation systems. For the ultra-low power consumption, it adopts four low-power features: 1) a 4-point scale-invariant generaliz... 展开 An ultra-low-power object matching processor is proposed for the autonomous micro air vehicle (MAV) navigation systems. For the ultra-low power consumption, it adopts four low-power features: 1) a 4-point scale-invariant generalized Hough transform (4P-SIGHT) to reduce the computational cost by 51%, 2) a feature streaming pipeline (FSP) to lower the operating frequency by 40%, 3) a Huffman and delta decoder (HDD) to reduce the memory readouts by 35.3%, and 4) a small-area and wide-operating-range 10-transistor level shifter (10T-LS) for the near-threshold voltage (NTV) operation. The proposed 2.0 object matching processor is fabricated using 65 nm CMOS technology and it consumes only 54 at 5 MHz operating frequency and 0.5 V supply voltage while processing QVGA resolution video in 30 fps. It is successfully applied to the MAV and shows 93.5% recognition accuracy for the autonomous navigation. It provides 9.35 better energy efficiency than previous state-of-the-art object matching processors. 收起