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obstacle_detection [2016/03/13 09:08] zyuan |
obstacle_detection [2019/04/25 14:08] |
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| - | We use the **[[Point Cloud Library PCL]][[http://pointclouds.org/documentation/]]** that aims at detecting obstacles (with Kinect). | ||
| - | ====== Objectif ====== | ||
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| - | 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]] | ||
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| - | 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) | ||
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| - | ===== package ===== | ||
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| - | The package: {{:pcl_detector.tar.gz|}} | ||
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| - | 1. Launch Kinect Sensor | ||
| - | * //roslaunch openni_launch openni.launch// | ||
| - | 2. Run | ||
| - | * //rosrun pcl_detector pcl_detector// | ||
| - | You can simulate the result by using rviz: | ||
| - | //rosrun rviz rviz// | ||
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| - | Choose the output topic "output" in type of "PointCloud2" | ||
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