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2022 ARC Annual Review

Welcome! The Automotive Research Center presents this event to bring together members of the automotive research community from across academia, government and industry to share our latest research developments. It is an opportunity to share ideas, discuss Army-relevant efforts, and to leverage and transfer our efforts to industry.


Agenda


2022 Day 1 - June 21

9:00 AM

Opening Remarks

The Honorable Gary Peters
United States Senate

Mr. Michael Cadieux
Director, U.S. Army Combat Capabilities Development Command’s Ground Vehicle Systems Center (GVSC)

9:20

Keynote:
DARPA RACER Program Update

Dr. Stuart Young
Program Manager, Defense Advanced Research Projects Agency (DARPA)

9:55

Keynote:
Aligning Model-based and Software Factory Approaches for Autonomous Ground Vehicle Development

Mr. Jim Tung
Mathworks Fellow, MathWorks
Mr. Kirsten McCane
Aerospace and Defense Industry Segment Manager, MathWorks

10:30

Break

10:45

Case Study:
Fast and Curious: How to Predict and Push Limits of Autonomous Mobility on Deformable Terrains

        Making autonomous vehicles able to navigate deformable terrains at operationally-relevant speeds is a critical need for military operations. We envision that achieving such speeds on deformable terrains requires accounting for terrain deformations with high accuracy both in the algorithms that navigate autonomous vehicles, and in the simulations used to develop and evaluate those algorithms. This, however, poses a major research challenge due to the trade-off between high accuracy and computational needs.
        This case study is a first step to address this grand challenge with both experimental and simulation components. A novel terrain-aware trajectory planning and control algorithm is deployed and run on an MRZR on soft soil to demonstrate the need and a solution for accurately accounting for deformable terramechanics in planning to safely navigate the vehicle at speed. Data from this demonstration, along with data from soil characterization experiments, is then leveraged to attempt recreation of this experimental vehicle performance in simulation. Two approaches for tire-terrain interaction modeling are utilized with different levels of fidelity, demonstrating the need for high-fidelity terrain representation in evaluating the vehicle navigation and mobility on complex granular terrain and the ARC’s solutions to make it computationally more tractable.
        Thus, the results support the vision that it is necessary but also possible to accurately represent deformable terrains in algorithms and simulations to enable high-speed autonomous off-road mobility.

11:30

Case Study:
No Time to Fail: Keeping multi-agent off-road teams on the move using a multi-scale hierarchical framework for task allocation and vehicle recharging

        Multi-agent off-road team allocation and task completion requires modeling and data analysis across a range of control hierarchies and model fidelities. In this case study, we leverage the outcomes from multiple ARC projects to complete a multi-scale hierarchical framework for task allocation and vehicle recharging. At the low-level, a high-fidelity vehicle and engine model takes vehicle control inputs and simulates the energy consumption, travel velocity, and thermal management of a vehicle and its components. At the mid-level, a single-agent planner considers the goal location and schedule for one agent and generates the travel path based on search-based path planning and model predictive control methods. The high-level team planner calls the single-agent planner and vehicle model to evaluate the path and costs between all task locations and generate a plan for task allocation and coordinated recharging. An ablation study is conducted to evaluate how the task allocation problem changes as a function of the charging behavior, vehicle path plans, and availability of high-fidelity vehicle and engine models. A practical simulation case study is designed to showcase the application of the complete hierarchical system.

12:10 PM

Lunch

1:30

Technical Session 1 (matrix of parallel sessions)

 

Session 1.A and Session 1.B

3:30

Poster Session and Reception
Reception begins at 4:30pm

6:30

Adjourn, Day 1


2022 Day 2 - June 22

9:00 AM

Plenary Remarks

Dr. Eric Michielssen
Associate Dean of Research and Louise Ganiard Professor of Engineering, University of Michigan

9:10 AM

Keynote:
The Future is Here: Modeling and Simulation Ecosystem of Research and Innovation for Off-Road Mobility and Operations

Dr. David Gorsich
Chief Scientist, U.S. Army Ground Vehicle Systems Center (GVSC)

Dr. Bogdan Epureanu
Director, Automotive Research Center

        The Automotive Research Center (ARC) is the U.S. Army's Center of Excellence for Modeling and Simulation (M&S) of Ground Systems. The Center has gone through several transformations in its history, and most recently there has been a focus on modeling autonomous systems, especially off-road. Through this transformation there has been an accent on partnering with other centers and industry, and leveraging investments. This year, we are in the process of engaging with new partners as well as operationalizing the Ground Vehicle M&S Alliance. In this presentation, we will discuss the vision for the alliance as an ecosystem of modeling and simulation research and innovation. In addition, we will discuss recent developments of capabilities in the ARC as well as share a few success stories of transitions of capabilities.

9:30

Panel Session:
The Importance of Societal and DEI-based Research in Autonomy

Panelists:
Dr. Susan Adams

Manager of Applied Cognitive Science Group, Sandia National Laboratory

Ms. Peggy Caveney
Model Based Design Supervisor, Ford Motor Company

Dr. Denise Rizzo
Deputy Chief Scientist, U.S. Army Ground Vehicle Systems Center (GVSC)

Moderator:
Dr. Kira Barton
Associate Director, Automotive Research Center

        To create autonomic ground vehicles that are capable, reliable, optimal, and survivable in a wide range of changing and challenging environments, we rely on understanding the interactive effects of technological and environmental elements, human factors, and social behavior. Similarly, human and social factors within our teams and in our research process influence what technology we are capable of creating and what impacts that technology can have. Thus, developing the skills to think critically about the human-technology interactions in our research teams and re-imagining how team interactions can be inclusive and supportive are key to moving us closer to the professional and personal goals we hold as engineers.

10:30

Break

10:45

Technical Session 2 (matrix of parallel sessions)

 

Session 2.A and Session 2.B

12:45 PM

Awards & Closing Remarks

1:00 Closing Reception
2:30

Day 2 Adjorns


Technical Talks Matrix

The Technical Talks allow ARC projects to report on their research goals and outcomes. Each talk will consist of a 15-minute presentation followed by 5-minute for Q&A.


2022 Day 1 - June 21

Technical Session 1

 

Session 1.A
Human Factors

Session Chairs: Victor Paul, Matt Castanier (GVSC)

Session 1.B
Perception, Planning, Teaming

Session Chairs: Mike Cole (GVSC)

1.30 PM Project 1.33, PI: Wang
Trust-based Symbolic Motion and Task Planning for Multi-robot Bounding Overwatch
Project 1.31, PI: Carruth
Comparison of Simulation and Physical Testing of Autonomous Ground Vehicles
1.50 Project 2.14, PI: Bethel
Dynamic Task Allocation and Understanding of Situation Awareness Under Different Levels of Autonomy in Closed-Hatch Military Vehicles
Project 1.35, PI: Bansal
Telerobotic Camera View-Frame Placement and Distributionally Risk-Receptive Network Interdiction Problems
2.10 Project 2.13, PI: Epureanu
Optimal Distribution of Tasks in Human-Autonomy Teams
Project 1.36, PIs: Ghaffari, Barton
Semantic Mapping in Dynamic Off-Road Environments
2.30 Project 2.12, PI: Ersal
Cognitive Modeling of Human Operator Behavior during Interaction With Autonomous Systems
Project 1.37, PI: Popa
Ultrasound-based perception in complex scenes using specialized convolutional neural networks
2.50 Project 2.16, PI: Chai
Situated Dialogue for Handling Unexpected Situation in Autonomous Driving Agents
Project 1.30, PI: Venkatachalam
Novel Data-Driven Algorithms for Autonomous Vehicle Path Planning Problems During Planning and Evaluation Stages
3.10 - 3.30 Project 2.15, PI: Mihalcea
In-the-wild Question Answering: Toward Natural Human-Autonomy Interaction
Project 5.20, PI: Epureanu
Dynamic Teaming of Autonomous Vehicles to Improve Operational Effectiveness of Vehicle Fleets

2022 Day 2 - June 22

Technical Session 2

 

Session 2.A
Materials, Assessment, Planning

Session Chairs: Katie Sebeck, Vamshi Korivi (GVSC)

Session 2.B
Quantum Computing, Learning, Requirements, Specifications, Trade Space Analysis

Session Chairs: Mike Cole (GVSC)

10.45 AM Project 3.18, PI: Barrett
Materials design of polycarbonates at the atomistic-scale with machine learning
Project 1.A73, PI: Veerapaneni
Continuous-Variable Quantum Approximate Optimization Algorithm: Application to Ground Vehicle Offroad Mobility
11.05 Project 2.A72/74, PI: Green
Assessing the Quality of Driving On and Off-Road Vehicles: Measures and Statistics of Driving Performance
Project 1.A81, PI: Veerapaneni
Tensor network approaches for fast and data efficient learning: applications to imitation learning from video data
11.25 Project 4.A87, PI: Ghasemi
Energy Efficiency Optimization and Control of a Fully Electric Off-Road Vehicle with Individual Wheel Drives
Project 1.A75, PI: Krovi
Deep Reinforcement Learning Approaches to CPS Vehicle Deployments
11.45 Project 3.A88, PI: Vantsevich
Technical Approaches and Analysis of Vehicle Conceptual Design for Mobility and Autonomous Mobility
Project 5.A78, PI: Rai
Computational Representation and Analysis of Mission and System Requirements
12.05 PM Project 1.A90, PIs: Mourelatos/Hu
Mobility Prediction of Off-Road Ground Vehicles Using a Dynamic Ensemble of NARX Models
Project 5.A79, PI: Mocko
A Formal Ontology and Simulation Model Library to enable Model Reuse and Integration
12.25 - 12.45 Projects 5.19 & 5.A71, PIs: Vasudevan, Epureanu
5.19: Adversarial Scene Generation for Virtual Validation and Testing of Off-Road Autonomous Vehicle Performance
5.A71: Building Unreal Engine Scenes from Recorded Data
Project 5.A80, PI: Turner
Exploring a Synthetic Tradespace through Decomposition and Coordination

Poster Session

Every ongoing ARC project contributes to the poster session at the afternoon of Day 1. It is an excellent opportunity to interact with researchers and network.

Poster 1.29 Remote Sensing Based Terrain Strength Characterization for the Next Generation NATO Reference Mobility Model Development

Poster 1.30 Novel Data-Driven Algorithms for Autonomous Vehicle Path Planning Problems During Planning and Evaluation stages

Poster 1.31 Evaluating Sensitivity of Autonomous Algorithms to Sensor Error and Environmental Conditions

Poster 1.33 Trust-based Symbolic Task and Motion Planning for Multi- Robot Bounding Overwatch

Poster 1.35 Novel Algorithms for Autonomous Telerobotic Surveillance and Reconnaissance System

Poster 1.36 Semantic Mapping in Dynamic Off-Road Environments

Poster 1.37 Ultrasound Based Perception Using ML Algorithms Trained in Synthetic Environments

Poster 1.38 Recognizing and Reconstructing Distorted and Obscured Perceptual Sensor Data Resulting from Soiling of the Sensor

Poster 1.A73 Quantum Computing for Off-road Mobility

Poster 1.A75 Cross-View Image Translation

Poster 1.A75 DNN Based Terrain Traversability Map Estimation and Path Planning

Poster 1.A81 Tensor Network Approaches for Fast and Data Efficient Learning: Applications to Imitation Learning From Video Data

Poster 1.A82 A Hybrid Controller with Observation and Decision Making for Autonomous Mobility Control System

Poster 1.A83 Semantic Segmentation with a Multi-Reservoir Echo State Network for Off-Road Terrain Perception

Poster 1.A85 Autonomous Vehicle Interactive Dynamics and Morphing with Mobility & Maneuver Self-Learning-and-Improvement

Poster 1.A89 Terrain Adaptive Autonomous Vehicles for Uncertain Off-Road Environments

Poster 1.A90 Reliable Deep Learning for Data-Driven Mobility Prediction under Uncertainty for Off-Road Autonomous Ground Vehicles

Poster 1.A91 Physics-based Robust, Adaptive and Scalable Control Algorithms for UGVs Operating at High-Speed in Adversarial Environments

Poster 2.12 Cognitive Modeling of Human Operator Behavior during Interaction with Autonomous Systems

Poster 2.13 Optimal Distribution of Tasks in Human-Autonomy Teams: Team Design and Strategy Learning with Reduced Load

Poster 2.14 Dynamic Task Allocation and Understanding of Situation Awareness Under Different Levels of Autonomy in Closed-Hatch Military Vehicle

Poster 2.15 In-the-wild Question Answering: Toward Natural Human-Autonomy Interaction

Poster 2.16 Language Communication and Collaboration with Autonomous Vehicles Under Unexpected Situations

Poster 2.17 Effects of Shared Mental Models and Information Amount on Situation Awareness for Human-Robot Teaming

Poster 2.A72 Effect of the Commander’s Interface, Crew Size, and Task Switching on Formation Change and Mission Performance

Poster 2.A74 Development of a Standard for Driving Performance Measures and Statistics

Poster 2.A92 A Spectator System for Virtual Experimentation on Military Robot Technology

Poster 2.A94 Situational Awareness & Trust Repair in Multi-Agent Human-Automation Teams

Poster 3.17 Enhanced Multiscale Off-Road Mobility Prediction Capability with Machine Learning Constitutive Modeling for Large Deformable Granular Terrain

Poster 3.18 Materials design of polycarbonates at the atomistic scale with machine learning

Poster 3.19 Intelligent ultrasound to adaptively control interfacial properties and reactions

Poster 3.20 Modeling of a Ground Vehicle Operating in Shallow Water

Poster 3.21 Design of Modular Origami Structures for Multifunctional Cloaking and Protection

Poster 3.22 Tire–mud interaction modeled using Smoothed Particle Hydrodynamics and Finite Element Analysis (SPH-FEA) techniques, and experimental validation

Poster 3.A84 Imaging and Modeling of Tire Displacements

Poster 3.A88 Autonomous Vehicle Design for Vehicle Operational Properties

Poster 4.36 Learning Enabled Mission Adaptation for a Hybrid Opposed Piston Engine

Poster 4.37 Risk Averse Vehicle Signature Management and Control to Enable Silent Mobility/Watch

Poster 4.A76 Integrated Transient Control and Thermal Management of Autonomous Off-Road Vehicle Propulsion Systems

Poster 4.A87 Maximizing Autonomous Mobility and Energy Efficiency on-the-go through Exteroceptive and Proprioceptive Self-Learning-and-Improvement

Poster 5.15 Autonomously Learning Mobility Limits

Poster 5.19 Adversarial Scene Generation for Virtual Validation and Testing of Off-Road Autonomous Vehicle Performance

Poster 5.20 Dynamic Teaming of Autonomous Vehicles to Improve Operational Effectiveness of Vehicle Fleets

Poster 5.A77 Energy Management of Multi-Scale Vehicles - Disturbance Decoupling Tube-Based Distributed Control of DC Microgrids

Poster 5.A77 Disaster Rescue & Recovery Mobile Microgrid Optimization

Poster 5.A78 Computational Representation and Analysis of Mission and System Requirements

Poster 5.A79 Model Repository and Integration Framework - Developing Domain Ontologies and an Integration Ontology to Support Modeling Composition

Poster 5.A80 Exploring a Synthetic Tradespace through Decomposition and Coordination


Contact: arc-event-inquiries@umich.edu