- Fuse Multiple Lidar Sensors Using Map Layers
Occupancy maps offer a simple yet robust way of representing an environment for robotic applications by mapping the continuous world-space to a discrete data structure. Individual grid cells can contain binary or probabilistic information about obstacle information. However, an autonomous platform may use a variety of sensors that may need to be combined to estimate both the current state of the platform and the state of the surrounding environment.
- Build Occupancy Map from Depth Images Using Visual Odometry and Optimized Pose Graph
This example shows how to reduce the drift in the estimated trajectory (location and orientation) of a monocular camera using 3-D pose graph optimization. In this example, you build an occupancy map from the depth images, which can be used for path planning while navigating in that environment.