Ros2 perception

Skill Leehyunbin0131/claude-ros2-skills/skills/ros2-perception

Claude Code skills for ROS 2 Jazzy — establish the unknowns first, verify against the installed system, prove the result ran.

Install

npx -y skills add Leehyunbin0131/claude-ros2-skills --skill ros2-perception

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What its author says it does

Copied from the file, not written here

Perception: image_transport, cv_bridge, vision_msgs, depth_image_proc, laser_geometry, pcl_ros.

SKILL.md

3.7 KB, 964 tokens by cl100k_base, as published. Nobody here has run it

ROS 2 Perception & Computer Vision Instructions (Ubuntu 24.04 LTS & ROS 2 Jazzy)

1. Documentation Entry Points

Any Jazzy package's API docs live at https://docs.ros.org/en/jazzy/p/<package>/ — build the URL from the package name rather than looking one up.

Packages in this domain: image_transport (transport plugins, compressed), cv_bridge (OpenCV conversion), vision_msgs (2D/3D detections), depth_image_proc (depth→cloud, registration), pointcloud_to_laserscan, laser_geometry (scan projection), pcl_ros (PCL bridge).

Verify message field names against the installation itself: ros2 interface show sensor_msgs/msg/Image.

2. Key Concepts & Patterns

A. `cv_bridge` OpenCV Conversion (C++)

#include <rclcpp/rclcpp.hpp>
#include <sensor_msgs/msg/image.hpp>
#include <sensor_msgs/image_encodings.hpp>
#include <cv_bridge/cv_bridge.hpp>
#include <opencv2/imgproc/imgproc.hpp>

void process_image(const sensor_msgs::msg::Image::ConstSharedPtr & msg) {
  cv_bridge::CvImagePtr cv_ptr = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8);
  cv::circle(cv_ptr->image, cv::Point(50, 50), 10, CV_RGB(255, 0, 0), 2);
  sensor_msgs::msg::Image::SharedPtr out_msg = cv_ptr->toImageMsg();
}

B. `pcl_ros` PointCloud Conversion (C++)

#include <sensor_msgs/msg/point_cloud2.hpp>
#include <pcl_conversions/pcl_conversions.h>
#include <pcl/point_types.h>
#include <pcl/filters/voxel_grid.h>

void filter_cloud(const sensor_msgs::msg::PointCloud2::SharedPtr msg) {
  pcl::PointCloud<pcl::PointXYZ>::Ptr pcl_cloud(new pcl::PointCloud<pcl::PointXYZ>);
  pcl::fromROSMsg(*msg, *pcl_cloud);

  pcl::PointCloud<pcl::PointXYZ>::Ptr filtered(new pcl::PointCloud<pcl::PointXYZ>);
  pcl::VoxelGrid<pcl::PointXYZ> sor;
  sor.setInputCloud(pcl_cloud);
  sor.setLeafSize(0.05f, 0.05f, 0.05f);
  sor.filter(*filtered);

  sensor_msgs::msg::PointCloud2 output_msg;
  pcl::toROSMsg(*filtered, output_msg);
}

3. Symptom -> Root Cause -> Action

Symptom	Likely root cause	Action
Image topic listed but callback never fires	QoS mismatch: camera drivers publish BestEffort, subscriber defaults Reliable	Subscribe with sensor-data QoS — C++ `rclcpp::SensorDataQoS()`, Python `rclpy.qos.qos_profile_sensor_data` (there is no `rclcpp` module in Python); confirm with `ros2 topic info <topic> -v`
`cv_bridge` throws encoding exception	Requested encoding doesn't match source (`bgr8` vs `rgb8`, `16UC1` depth)	Use `toCvCopy(msg, msg->encoding)` (passthrough) or convert explicitly; never assume `bgr8` for depth
Depth values look 1000x off or all ~0	`16UC1` is millimeters, `32FC1` is meters — unit confusion	Check `msg->encoding` before scaling; divide 16UC1 by 1000.0 for meters
Point cloud misaligned with the RGB image	Depth not registered into the color optical frame	Use the `depth_registered` topic or `depth_image_proc` register node; verify both `frame_id`s
`pointcloud_to_laserscan` outputs empty scans	`min_height`/`max_height` band excludes all points, or `target_frame` transform missing	Widen the height band around the sensor's actual Z; check TF to `target_frame`
Detection boxes drawn at wrong image positions	Processing the rectified topic but projecting with the raw camera matrix (or vice versa)	Pair `image_rect` with `P` (projection) matrix, raw `image` with `K`; don't mix
High CPU from image subscribers	Subscribing raw full-resolution images over the network	Use `image_transport` compressed transport, or throttle/downscale before processing