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Corrected a typo in Radar Sensor section (#3598) 

* Corrected a typo in Radar Sensor section

* Update CHANGELOG.md

Co-authored-by: Axel1092 <35765780+Axel1092@users.noreply.github.com>
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Adrian Jenkins 2020-11-23 11:44:04 -05:00 committed by GitHub
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CHANGELOG.md
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@ -18,6 +18,7 @@
* Fixed the lack of determinism on the output of raycast sensors
* Fixed bug in the actor's id returned by the semantic lidar
* Fixed dependency of library **Xerces-c** on package
* Fixed minor typo in the simulation data section of the documentation
* Fixed the `config.py` to read the `.osm ` files in proper `utf-8` encoding
## CARLA 0.9.10

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Docs/tuto_G_retrieve_data.md
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@ -563,7 +563,7 @@ The attributes of this sensor mostly set the way the lasers are located.
* __`range`__ is the maximum distance for the lasers to raycast.
* __`points_per_second`__ sets the the amount of points to be captured, that will be divided between the channels stated.
The script places the sensor on the hood of the car, and rotated a bit upwards. That way, the output will map the front view of the car. The `horizontal_fov` is incremented, and the `vertical_fov` diminished. The area of interest is specially the height were vehicles and walkers usually move on. The `range` is also changed from 100m to 10m, in order to retrieve data only right ahead of the vehicle.
The script places the sensor on the hood of the car, and rotated a bit upwards. That way, the output will map the front view of the car. The `horizontal_fov` is incremented, and the `vertical_fov` diminished. The area of interest is specially the height where vehicles and walkers usually move on. The `range` is also changed from 100m to 10m, in order to retrieve data only right ahead of the vehicle.
The callback is a bit more complex this time, showing more of its capabilities. It will draw the points captured by the radar on the fly. The points will be colored depending on their velocity regarding the ego vehicle.