If you have high-quality 3D sensors (or in some cases, good-enough 2D cameras) and usable IMU/odometry, you can assemble quite reasonable 3D models for many sma

If you have high-quality 3D sensors (or in some cases, good-enough 2D cameras) and usable IMU/odometry, you can assemble quite reasonable 3D models for many small environments. The biggest challenges in a home environment are that many items we want in our houses (stainless steel appliances, chairs with thin legs, glass anything, reflective floor materials) are almost pathologically bad from a computer vision standpoint and are very hard to see and avoid in an uncontrolled household setting. Vision-based navigation against a known environment is doable with reasonable reliability, but adding fixed markers or positioning systems goes a long way towards robustness.