According to the World Health Organization, visual impairment is estimated to affect approximately 2.2 billion people worldwide. The visually impaired must currently rely on navigational aids to replace their sense of sight, like a white cane or GPS (Global Positioning System) based navigation, both of which fail to work well indoors. The white cane cannot be used to determine a user's position within a room, while GPS can often lose connection indoors and does not provide orientation information, making both approaches unsuitable for indoor use. Therefore, this research seeks to develop a 3D-imaging solution that enables contactless navigation through a complex indoor environment. The device can pinpoint a user's position and orientation with 31% less error compared to previous approaches while requiring only 53.1% of the memory, and processing 125% faster. The device can also detect obstacles with 60.2% more accuracy than the previous state-of-the-art models while requiring only 41% of the memory and processing 260% faster. When testing with human participants, the device allows for a 94.5% reduction in collisions with obstacles in the environment and allows for a 48.3% increase in walking speed, showing that my device enables safer and more rapid navigation for the visually impaired. All in all, this research demonstrates a 3D-based navigation system for the visually impaired. The approach can be used by a wide variety of mobile low-power devices, like cell phones, ensuring this research remains accessible to all.