ukf-sensor-fusion

Name: ukf-sensor-fusion
Availability: InStock
Author: wimble

Configure robot_localization UKF parameters for non-linear sensor fusion in ROS 2.

18|2|Updated Apr 20, 2026

Search Tags:#navigation #ros2 #sensor-fusion #kalman-filter #robot_localization #ukf #state-estimation

Ready to run

npx skills add https://github.com/wimblerobotics/ros2-copilot-skills --skill ukf-sensor-fusion

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ukf-sensor-fusion
Source: https://github.com/wimblerobotics/ros2-copilot-skills/tree/main/ukf-sensor-fusion
Command: npx skills add https://github.com/wimblerobotics/ros2-copilot-skills --skill ukf-sensor-fusion

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

UKF-based sensor fusion for the robot_localization package enables robust state estimation in non-linear systems where EKF linearization is insufficient.

Core Features & Use Cases

UKF parameters: alpha, kappa, and beta control sigma-point distribution for nonlinear propagation.
Configurable node: ukf_filter_node with the same input structure as EKF, including odom, imu, and map frames.
Practical guidance: switch between EKF and UKF by swapping the executable in the launch file, enabling direct comparison on real or simulated data.

Quick Start

Load the UKF configuration by enabling ukf_filter_node with alpha, kappa, and beta and switch to ukf_node in the launch file.

Frequently Asked Questions about ukf-sensor-fusion

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

FAQPage Schema

How do I configure UKF parameters for robot_localization sensor fusion in ROS 2?▼

To configure UKF sensor fusion in ROS 2, set the alpha, kappa, and beta parameters in the YAML file for the ukf_filter_node to control sigma-point distribution for nonlinear state estimation.

When should I use a UKF instead of an EKF for robot state estimation?▼

You should use a UKF for state estimation when your robotic system is highly non-linear and EKF linearization is insufficient, as the UKF applies sigma-point distribution for robust nonlinear propagation.

How do I switch from EKF to UKF in the robot_localization package?▼

To switch from EKF to UKF in robot_localization, swap the executable to ukf_node in your launch file, keeping the same input structure for odom, imu, and map frames to enable direct comparison.

Can I use robot_localization UKF for a diff-drive robot?▼

Yes, the robot_localization UKF explicitly supports diff-drive and other non-linear platforms requiring robust state estimation across varying sensor inputs like odom and imu data.

What frame mappings are required for ukf_filter_node configuration?▼

The ukf_filter_node configuration requires standard frame mappings including map, odom, and base_link to correctly process sensor fusion inputs from varying sources.