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 Mr. Michael Cadieux
|
9:20 | Keynote: Dr. Stuart Young |
9:55 | Keynote: Mr. Jim Tung |
10:30 | Break |
10:45 | Case Study: 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. |
11:30 | Case Study: 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 |
6:30 | Adjourn, Day 1 |
2022 Day 2 - June 22
9:00 AM | Plenary Remarks Dr. Eric Michielssen |
9:10 AM | Keynote: Dr. David Gorsich Dr. Bogdan Epureanu 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: Panelists: Ms. Peggy Caveney Dr. Denise Rizzo Moderator: 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 Session Chairs: Victor Paul, Matt Castanier (GVSC) | Session 1.B 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 Session Chairs: Katie Sebeck, Vamshi Korivi (GVSC) | Session 2.B 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