<![CDATA[Visually impaired individuals often face difficulties in performing daily activities due to their limited visual senses. In order for the visually impaired to navigate without collision, a device with a system to detect obstacles in its surroundings is needed. In this study, a assistive cane has been designed that utilizes a fuzzy system based on the Mamdani model to detect obstacles. The main controller is an ESP32, equipped with two LiDAR VL53L1X sensors as inputs, capable of detecting obstacles up to 4 meters away. Family members can monitor the position of the visually impaired cane integrated with GPS through an Android application. The results of this study obtained an average error rate on the reading of two LiDAR Time of Flight Sensor devices with the VL53L1X type against obstacles in front of the stick of 0.00136% and sensor one has an accuracy of 99.85925% and sensor two has an accuracy of 99.862175% against the distance of obstacles in front of the stick. The blind cane made has an average battery life of 1 hour 35 minutes 83 seconds for random navigation, namely there are obstacles and no obstacles in front of the stick. Overall, the system can run well. The blind cane can classify the level of obstacles in front with the category of close at a distance of 0 - 100 cm, medium 101 - 150 cm, and far 150 - 400 cm]]>
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