Difference between revisions of "Obstacle Detection"
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Complex application: a robot uses a [[Lidar#3D Lidar|3D lidar]] to scan its surroundings and passes the generated point cloud to a SLAM algorithm to update a map of its environment. | Complex application: a robot uses a [[Lidar#3D Lidar|3D lidar]] to scan its surroundings and passes the generated point cloud to a SLAM algorithm to update a map of its environment. | ||
− | [[ | + | [[Sensor Selection|Sensor selection]] is a complex topic and depends on many factors and considerations.<br /> |
==List of Commonly Used Sensors== | ==List of Commonly Used Sensors== |
Latest revision as of 16:21, 9 April 2021
Obstacle detection is the use of sensors and software to identify obstacles around the robot. Obstacle detection plays a critical role in preventing collisions, mapping/SLAM, and generating information used by navigation and path planning algorithms.
Simple application: a robot reads output from a front-mounted IR or ultrasonic distance sensor to detect obstacles in front of itself and uses this information to stop before a collision happens.
Complex application: a robot uses a 3D lidar to scan its surroundings and passes the generated point cloud to a SLAM algorithm to update a map of its environment.
Sensor selection is a complex topic and depends on many factors and considerations.
List of Commonly Used Sensors
Contact Switch
Camera
Depth Camera