What is a sparse 3D map?

A sparse 3D map is a simplified three-dimensional representation created by autonomous mobile robots that consists of discrete data points highlighting distinctive features in the environment. Unlike dense 3D maps, which capture detailed surfaces and volumes, sparse maps form a “cloud” of key points that provide enough spatial information for certain operations without full environmental detail.

What are sparse 3D maps used for?

Sparse 3D maps are primarily used for tasks such as robot localization, where knowing the position relative to key landmarks is sufficient. These maps require less computational power and storage than dense maps, making them efficient for real-time navigation and resource-limited scenarios. While they do not provide a complete picture of the environment, sparse maps are a critical component in many simultaneous localization and mapping (SLAM) systems.