

IM1R_ROS1_Driver
ROS 1 driver for DAISCH IM1R. C++ implementation compatible with Ubuntu 18.04/20.04 (Melodic & Noetic).
Cost / License
- Free
- Open Source (BSD-3-Clause)
Platforms
- Linux
Features
Tags
IM1R_ROS1_Driver News & Activities
Recent activities
- Daisch added IM1R_ROS1_Driver
Daisch added IM1R_ROS1_Driver as alternative to DAISCH IM1R ROS2 Driver
IM1R_ROS1_Driver information
What is IM1R_ROS1_Driver?
Overview DAISCH IM1R ROS1 Driver is an open-source software package designed to seamlessly integrate high-precision inertial measurement units (IMUs) into the Robot Operating System (ROS) ecosystem. It acts as a robust, low-latency communication bridge that parses raw serial data from the hardware sensor and transforms it into standardized developer-friendly formats within ROS 1 environments.
Key Features
Standard ROS Compatibility: Directly publishes standard ROS message types, specifically sensor_msgs/Imu, ensuring out-of-the-box compatibility with mainstream ROS localization, navigation, and state-estimation stacks.
High-Rate Data Streaming: Optimally parses serial data streams to deliver high-frequency, low-latency linear acceleration and angular velocity readings required for real-time robotic controls.
Flexible Parameter Configuration: Allows developers to easily customize runtime parameters—such as serial port paths, baud rates, and coordinate frame IDs—directly via standard ROS launch files without recompiling the source code.
Lightweight and Efficient: Written with optimization in mind, ensuring minimal CPU overhead on embedded computing platforms typically used in field robotics.
Developer-Friendly Architecture: Open-source codebase with a clean structure, making it highly extensible for researchers and engineers who need to customize sensor data pipelines or implement unique multi-sensor fusion architectures.
Target Applications This driver package is highly recommended for developers and robotics researchers working on:
Autonomous driving vehicle localization and dead reckoning.
Unmanned Aerial Vehicles (UAVs) and ground robotics navigation.
SLAM (Simultaneous Localization and Mapping) tracking pipelines.
Multi-sensor fusion projects (e.g., combining IMU with LiDAR or Cameras).

