Determination of trajectories using IKZ/CF inertial navigation: Methodological proposal.

Area of Science:

• Robotics and Autonomous Systems
• Navigation and Control Systems

Background:

• Inertial Navigation Systems (INS) are crucial for autonomous navigation but suffer from drift errors.
• Existing solutions often integrate absolute references (e.g., GPS), which are not always feasible.
• Reducing INS drift without absolute references is a significant challenge.

Purpose of the Study:

• To present an improved methodology for tracking and localization of moving objects.
• To reduce drift errors in INS by integrating the IKZ method with a complementary filter (CF).
• To enhance the handling characteristics of INS for real-world applications.

Main Methods:

• Integration of the IKZ methodological proposal with a complementary filter (CF).
• Development of a novel approach to mitigate drift errors in INS.
• Testing the IKZ/CF methodology using raw data from an MPU-9255 sensor.

Main Results:

• The proposed IKZ/CF integration effectively reduces drift errors in INS.
• The methodology maintains restrictive properties for drift error control.
• Significant improvements in system handling characteristics for real applications were observed.

Conclusions:

• The IKZ/CF integration offers a robust solution for autonomous navigation challenges.
• This method provides an effective alternative when absolute references are unavailable.
• The findings demonstrate the practical viability of the IKZ/CF approach for mobile object tracking and localization.