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visual-odometry

Estimate robot ego-motion from camera streams for ROS 2 visual odometry.

18|2|Updated Apr 20, 2026
Search Tags:#ros2#robotics#slam#odometry#ekf#visual-odometry
One-click install
npx skills add https://github.com/wimblerobotics/ros2-copilot-skills --skill visual-odometry
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: visual-odometry
Source: https://github.com/wimblerobotics/ros2-copilot-skills/tree/main/visual-odometry
Command: npx skills add https://github.com/wimblerobotics/ros2-copilot-skills --skill visual-odometry

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Visual odometry estimates robot motion from camera frames in ROS 2, providing odometry data to feed localization and sensor fusion; it enables ego-motion estimation when wheel odometry is unavailable or unreliable.

Core Features & Use Cases

  • Supports multiple backends: RTAB-Map VO, OAK-D VIO, ORB-SLAM3, and libviso2-based pipelines.
  • Provides odometry output for EKF fusion with wheel odometry and IMU.
  • Use case: fused localization on robots with monocular or stereo cameras; VO data supplements wheel odometry in low-slip conditions, or for scale-aware navigation.

Quick Start

Configure your ROS 2 workspace to run a VO backend (rtabmap_odom, viso2_ros, or ORB-SLAM3) and publish /vo/odometry for EKF fusion.

Frequently Asked Questions about visual-odometry

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I estimate robot ego-motion using visual odometry in ROS 2?▼

Visual odometry estimates robot ego-motion by processing camera streams to produce odometry data. In ROS 2, this provides navigation input when wheel odometry is unavailable or unreliable.

Can I fuse visual odometry with wheel odometry using an EKF?▼

Yes, visual odometry can be fused with wheel odometry and IMU data using an EKF. The pipeline publishes a /vo/odometry topic to supplement wheel odometry for scale-aware localization.

Does this visual odometry approach support stereo and visual-inertial setups?▼

Yes, visual odometry supports monocular, stereo, and visual-inertial setups. It integrates multiple backends including RTAB-Map, ORB-SLAM3, OAK-D VIO, and libviso2 to handle different camera configurations.

What ROS 2 packages do I need to run ORB-SLAM3 or RTAB-Map for odometry?▼

You need specific ROS 2 packages for each backend, such as rtabmap_odom, viso2_ros, or ORB-SLAM3. You must configure your workspace to run a backend and publish compatible camera topics.

When should I use visual odometry instead of relying on wheel odometry?▼

Visual odometry is ideal for low-slip conditions where wheel odometry is unreliable or unavailable. It provides scale-aware navigation by supplementing wheel data with fused camera-based motion estimates.

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