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obstacle_detection [2016/03/13 08:56]
zyuan
obstacle_detection [2019/04/25 14:08] (current)
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 We use the **[[Point Cloud Library PCL]][[http://​pointclouds.org/​documentation/​]]** ​ that aims at detecting obstacles (with Kinect). ​ We use the **[[Point Cloud Library PCL]][[http://​pointclouds.org/​documentation/​]]** ​ that aims at detecting obstacles (with Kinect). ​
 +====== Objectif ======
 +
 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. 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]]+  * 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: ​ 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)+**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: +===== package =====
-$ rosrun rviz rviz +
-Choose the output topic "​output"​ in type of "​PointCloud2"​ +
- +
-TODO: add FindingBlob to optimize the results.+
  
 The package: {{:​pcl_detector.tar.gz|}} The package: {{:​pcl_detector.tar.gz|}}
  
-To use it: 
 1. Launch Kinect Sensor 1. Launch Kinect Sensor
-$roslaunch openni_launch openni.launch+  * //roslaunch openni_launch openni.launch//
 2. Run  2. Run 
-$rosrun pcl_detector pcl_detector+  * //rosrun pcl_detector pcl_detector// 
 + 
 +==== Simulation ==== 
 + 
 +You can simulate the result by using rviz: 
 +  * //rosrun rviz rviz// 
 + 
 +Choose the output topic "​output"​ in type of "​PointCloud2"​ 
 + 
  • obstacle_detection.1457859395.txt.gz
  • Last modified: 2019/04/25 14:08
  • (external edit)