Self-Powered Wireless Sensing Platform for Vehicle Attitude Control

Project Summary

Principal Investigators

Nizar Lajnef, Michigan State University

Co-PIs

Mahmood Haq, Satish Udpa, Shanelle Foster, Michigan State University

Students

James Roulo, James Morrison, Michigan State University

Government

Jill Goryca, U.S. Army GVSC

Project #1.A108 duration Q4 2022 - Q4 2024.

Autonomous vehicles (AVs) rely on sensors such as global navigation satellite systems (GNSS), light detection and ranging (LiDAR), and inertial measurement units (IMUs) to navigate and perceive their environment. However, little attention has been given to the interaction between vehicles and terrain, particularly on uneven surfaces where soil properties play a critical role. Variations in shear strength, bearing capacity, and soil deformation significantly affect vehicle performance, especially under dynamic conditions.

Road profile irregularities on rough terrains introduce challenges beyond standard suspension adjustments. To ensure reliable autonomous operation, there is a pressing need to incorporate real-time terrain data into vehicle control algorithms. By doing so, stability and maneuverability can be actively optimized in response to changing soil conditions.

This project focuses on developing a sensor platform designed to address this need. The sensing system will directly measure key soil parameters such as shear modulus, shear strength, and failure limits, feeding real-time data into vehicle control algorithms. These insights will allow for the back-calculation of maneuvering forces acting on the vehicle and enable advanced control strategies to adjust suspension systems for improved dynamic stability. By integrating this sensor platform into vehicle control systems, the project aims to bridge the gap between terrain interaction and vehicle performance, ensuring safe and efficient autonomous navigation on challenging terrains.

This project focuses on addressing the problem of soil-vehicle interaction to determine soil properties in real time during vehicle operation. The work emphasizes the creation of an integrated system that combines advanced sensing hardware with computational tools to enhance vehicle stability and performance on varying terrains. The primary objectives of this phase are as follows:

Design and Development of a Prototype Sensing Apparatus: A sensing apparatus is designed and prototyped for attachment to a vehicle. The apparatus has strain and force sensors to extract critical soil properties such as shear modulus, shear strength, and bearing capacity during operation. The system is intended to operate reliably under dynamic conditions and provide high-resolution, real-time data for integration into vehicle control algorithms.

Implementation of a Simplified, Computationally Efficient Model: A computationally efficient model is developed as firmware to process real-time sensor data onboard the vehicle. This model is designed to back-calculate soil properties from strain and force measurements at a rate of at least 100 computations per second. The processed data supports dynamic control adjustments, ensuring stability and maneuverability on challenging terrain.

Development of a Computational Method for Data Verification and Soil Simulation: A computational method is developed to verify experimental data collected by the sensing apparatus. This method also generates synthetic data for various soil types and conditions that cannot be practically tested experimentally. Combining experimental and simulated data creates a comprehensive database of soil properties to support model training and validation.

1.A108