Differences
This shows you the differences between two versions of the page.
Next revision | Previous revision Next revision Both sides next revision | ||
obstacle_detection [2016/03/10 13:51] zyuan created |
obstacle_detection [2016/03/13 08:59] zyuan |
||
---|---|---|---|
Line 1: | Line 1: | ||
- | We use the package pcl | + | We use the **[[Point Cloud Library PCL]][[http://pointclouds.org/documentation/]]** that aims at detecting obstacles (with Kinect). |
+ | We catched the depth data and tranformed to point cloud. Then we filter that object which is higher than the ground. We projected this result to create a 2D image. By using this image, we can send back reference position of an obstacle. | ||
+ | You can also take a look to the tutorial:[[http://wiki.ros.org/pcl/Tutorials]] | ||
+ | |||
+ | Calibration Parameters for the calculation of 3D coordinates from the raw image measurements include: | ||
+ | The height of Kinect. | ||
+ | |||
+ | (In addition, we found that y-axis of the point cloud corresponds to the height, means the z-axis for a tf-tranform of Kinect Sensor) | ||
+ | |||
+ | |||
+ | You can simulate the result by using rviz: | ||
+ | //rosrun rviz rviz// | ||
+ | |||
+ | Choose the output topic "output" in type of "PointCloud2" | ||
+ | |||
+ | |||
+ | The package: {{:pcl_detector.tar.gz|}} | ||
+ | |||
+ | 1. Launch Kinect Sensor | ||
+ | * //roslaunch openni_launch openni.launch// | ||
+ | 2. Run | ||
+ | * //rosrun pcl_detector pcl_detector// |