Current indoor perception systems fail to detect corner cases such as glass and mirror-like surfaces. Researchers have addressed these corner cases, but have not fully integrated these solutions into an efficient system. Using LiDAR, radar, and RGB-D camera technology with machine learning and SLAM algorithms, this team developed a handheld indoor perception system that accurately maps its environment and is robust to edge cases such as mirrors and glass.