February 2020
Intermediate to advanced
432 pages
10h 50m
English
Content preview from Hands-On ROS for Robotics Programming
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Costmaps for safe navigation
The costmap for robot navigation arises from the combination of the robot's pose, estimated from the odometry data (encoders) and the IMU sensor, the perception of objects and obstacles in the environment using the distance sensor and LDS, and the occupancy grid map (OGM) obtained from the SLAM technique.
These sources of information provide as output a joint measurement of obstacle areas, probable collisions, and the movable area for the robot. There is a global costmap and a local one. The global one accounts for the navigation path using the fixed map obtained through SLAM, while the local version allows the robot to deal with the fine-grained details of its immediate environment to move around obstacles and ...
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