ROS learning note

 

killall -9 roscore
killall -9 rosmaster

 To add the workspace to your ROS environment you need to source the generated setup file:

 

$ . ~/catkin_ws/devel/setup.bash
### YOLOv11 ROS Package Download and Installation For downloading and installing the YOLOv11 ROS package, it is important to note that as of now, there might not be an official release specifically named “YOLOv11”. However, assuming this refers to a specific version or variant within the YOLO family supported by some community contributions for ROS integration, one can follow general guidelines adapted from existing practices with other versions like YOLOv3, YOLOv4, etc. To proceed: #### Environment Setup Ensure the environment supports ROS packages effectively. Windows users have found significant ease in setting up ROS environments through WSL (Windows Subsystem for Linux), which allows running Ubuntu alongside native Windows applications without dual-booting[^1]. This setup facilitates accessing almost all mainstream ROS distributions conveniently. #### Locating Suitable Packages Since direct references to a "YOLOv11" ROS package are sparse, searching repositories such as GitHub becomes essential. Look for projects tagged under `ros`, combined with keywords related to YOLO object detection frameworks. Community-driven ports often provide detailed README files explaining how these models integrate into ROS ecosystems. #### Dependency Management When dealing with dependencies required by deep learning-based detectors like those based on YOLO architectures, ensure libraries necessary for compilation and execution—such as GLOG—are correctly installed and accessible during build processes. For instance, paths containing `.so` dynamic link libraries should be included in system library search paths so tools like CMake used in ROS workspaces recognize them properly[^2]. ```bash export LD_LIBRARY_PATH=/usr/lib/x86_64-linux-gnu/:$LD_LIBRARY_PATH ``` This command adds `/usr/lib/x86_64-linux-gnu/` directory where common dependency files reside to the runtime linker's path ensuring executables locate shared objects at launch time. #### Building From Source Code If no pre-built binary exists matching requirements exactly, consider cloning repository sources directly then building locally using Catkin workspace management commands provided by ROS. Follow instructions closely regarding Python virtual environments if specified; they help manage isolated sets of dependencies crucial when working across different AI model iterations.
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