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Vehicle Controls & Behaviors

Annual Plan

A Hybrid Controller with Observation and Decision Making for Autonomous Mobility Control System

Project Team

Principal Investigator

Vladimir Vantsevich, University of Alabama at Birmingham


Jill Goryca, Amandeep Singh, U.S. Army GVSC


Jesse Paldan (staff), UAB


Tom Canada, Southern Service Company


Masood Ghasemi (Postdoc), UAB

Project Summary

Project begins mid-2020.

The purpose of this project is to develop research fundamentals of a autonomous mobility control system (AMCS) with:

  1. an adjustable mobility control algorithm that is able to effectively operate in different severe terrains within an appropriate response time and, thus, to prevent the tire spinning,
  2. observation algorithms that are able to provide on-line states of the locomotion module’s normal, longitudinal, and rotational dynamics, and
  3. an Artificial Intelligence (AI) - based learning component that is able to learn from the observers’ data in real-time and improve/mature the mobility control parameters .

The goal is to mathematically design and demonstrate in computational simulations the autonomous mobility control system that functionally integrates the above-listed three components. This will be done for a locomotion module that is an assembly unit/corner of a Joint Light Tactical Vehicle (JLTV).

AMCS schematic

Experimental and analytical data researched in “Instant Tire Slippage Characterization with Digital Image Correlation for Autonomous Mobility Applications” will be used in this project.