ACEINNA announces a new video on the ACEINNA YouTube Video Channel – “All About the New ACEINNA OpenIMU Package.”
This short video provides a quick and easy overview of ACEINNA’s new OpenIMU package.
ACEINNA’s OpenIMU solution consists of three key parts.
First is a family of Inertial Measurement Units consisting of three high-accuracy accelerometers, three high-accuracy gyros, and a powerful ARM Coretex. Zoom in on OpenIMU and OpenIMU CAN Second is an OpenSource tool chain and reference code for programming the IMU. It consists of everything from basic download and debug to reference implementations of loosely-coupled GPS/INS. Third is a full Developer Site and tools with charting, graphing and even algorithm simulation.
“OpenIMU enables advanced, easy-to-deploy localization and navigation algorithm solutions for a fraction of the time and cost of traditional methods. OpenIMU's combination of open-source software and low-cost hardware enables rapid development of advanced solutions for drones, robotics, and autonomous applications,” explains Mike Horton, CTO of ACEINNA. “OpenIMU is a first of its kind, professionally supported, open-source GPS/GNSS-aided inertial navigation software stack for low-cost precise navigation applications.”
The OpenIMU Development hardware development kit includes JTAG-pod, precision mount fixture, EVB, and an OpenIMU300 module. The OpenIMU module features ACEINNA’s 5 deg/Hr, 9-Axis gyro, accelerometer, and magnetometer sensor suite with an onboard 180MHz ARM Coretex floating-point CPU. The IMU is delivered in a small (24x37x9.5 mm), easy to integrate module that operates from 2.7-5.5V DC.
This freely downloadable stack includes:
- FreeRTOS-based data collection and sampling engine
- Performance-tuned, real-time, navigation-grade GPS/INS Kalman Filter library
- Free IDE/compiler tool chain based on Visual Studio Code
- JTAG debugging for debugging code loaded on IMU
- Data logging, graphing, Allen Variance plots, and maps,
- Extensive documentation
- Robust simulation environment with advanced sensor error models