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Related Experiment Video

Updated: May 23, 2026

Using Micro-Electro-Mechanical Systems (MEMS) to Develop Diagnostic Tools

Using Micro-Electro-Mechanical Systems (MEMS) to Develop Diagnostic Tools

Published on: October 1, 2007

Improving planetary rover attitude estimation via MEMS sensor characterization.

Javier Hidalgo¹, Pantelis Poulakis, Johan Köhler

¹Centro de Automática y Robótica, UPM-CSIC, José Gutiérrez Abascal 2, Madrid 28006, Spain. jhidalgo@etsii.upm.es

Sensors (Basel, Switzerland)

|March 23, 2012

Summary

This summary is machine-generated.

This study introduces a complete methodology for characterizing and modeling Micro Electro-Mechanical Systems (MEMS) sensors for space applications. The approach ensures reliable performance in planetary robotics through detailed error analysis and sensor fusion integration.

Keywords:

attitude estimation inertial measurement unit (IMU)inertial navigation system (INS)micro-electro-mechanical systems (MEMS)planetary rover sensor characterization sensor fusion

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Last Updated: May 23, 2026

Using Micro-Electro-Mechanical Systems (MEMS) to Develop Diagnostic Tools

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Published on: October 1, 2007

Easy and Accurate Mechano-profiling on Micropost Arrays

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Published on: November 17, 2015

Area of Science:

Space Engineering
Robotics
Sensor Technology

Background:

Micro Electro-Mechanical Systems (MEMS) offer advantages for spacecraft, including robustness, low power, and small size.
A gap exists in understanding MEMS sensor performance and testing, particularly for planetary robotics applications.

Purpose of the Study:

To present a complete, reproducible methodology for MEMS sensor characterization and modeling.
To address the need for detailed sensor error analysis and integration into sensor fusion schemes for space applications.

Main Methods:

Described a comprehensive approach encompassing all intermediate steps, tools, and laboratory equipment.
Detailed the process of sensor error characterization and modeling.
Explained the integration of characterized sensors into a sensor fusion scheme.

Main Results:

Verified the methodology with novel high-grade MEMS inertia sensors.
Demonstrated promising results when applying the approach to exemplary planetary rover platforms.
Validated the effectiveness of detailed sensor characterization and filtering for optimal performance.

Conclusions:

The developed methodology provides a robust framework for MEMS sensor characterization and modeling in space applications.
Accurate sensor characterization and fusion are critical for achieving high performance in planetary robotics.
The approach offers a significant advancement for the reliable deployment of MEMS sensors in space missions.