Navigation & SLAM

Costmap

A costmap is a grid-based representation of the environment in which each cell stores a traversal cost, typically built from occupancy data with obstacles marked lethal and surrounding cells inflated by the robot's footprint and a safety margin. Layered costmaps, as in ROS navigation stacks like Nav2, compose static maps, live sensor obstacles, and semantic or social layers. Planners search the costmap for minimum-cost, collision-free paths.

Why it matters for physical AI

Costmaps remain the practical interface between perception and motion for mobile robots, and learned semantic layers, such as terrain traversability predicted by neural networks, plug naturally into this representation.