Date: September 9-10-11, 2025.
Location: DeLuca Forum, Discovery Building, University of Wisconsin-Madison – 330 N Orchard St, Madison, WI 53715.
Organizers: Dan Negrut, Radu Serban, and Luning Bakke, University of Wisconsin-Madison.
Event Sponsors: National Science Foundation, Brian Eckrose Foundation, Komatsu Corporation.
Registration Link: https://charge.wisc.edu/GraingerInstitute/magic.
Registration Fee: $150 for industry participants; free for academia, federal/state employees, and consortium members.
At its 13th edition, this year’s MaGIC meeting emphasizes Digital Twin and AI technologies in fields such as terramechanics, mechatronics, bio-robotics, geomechanics, and embodied AI. The event is focused equally on terrestrial and extraterrestrial applications. This is an informal gathering that seeks to bring together individuals from industry, academia, and research labs in a collaborative “let’s learn from each other” environment. The goal is to facilitate technology transfer and promote cross-pollination between industry and academia within a pre-competitive setting.
Overview of the program:
Day 0: Tuesday, September 9, 2025: Chrono tutorials, for those contemplating using the Chrono simulator in their work.
Day 1: Wednesday, September 10, 2025: invited talks. Student poster session in the late afternoon.
Day 2: Thursday, September 11, 2025: invited talks.
NOTE: This event is free for participants from (1) state or federal institutions, (2) companies that are members of the Machine-Ground Interaction Consortium, and (3) academia. Otherwise, the registration is $150/person. Contact Dan Negrut at negrut@wisc.edu if you are a participant from a small company who can’t afford the registration fee.
The MaGIC 2025 will have 20 to 25 speakers, amongst them (ordered alphabetically):
– Ramchander Bhaskara, Texas A&M: navigation filters, signal processing, computer vision, space robotics
– Akshat Dave, MIT Media Lab: computer vision, inverse graphics, polarization sensing
– Ryan Denney, US Army ERDC: CFD, fluid-solid interaction problems
– [keynote] Daniel Goldman, Georgia Tech: biomechanics, neuromechanics, granular media, robotics, robophysics
– [keynote] David Gorsich, US Army GVSC: digital engineering, applied math, terramechanics
– [keynote] Terry Fong, NASA Ames Research Center: robotics, extraterrestrial exploration (VIPER mission)
– Kaiyu Hang, Rice University: robotics manipulation
– Heather Jones, Carnegie Mellon University: robotics, lunar exploration (Moon Ranger rover)
– Krishna Kumar, UT-Austin: data driven methods, geotechnics, machine learning in numerical methods
– Ying Li, UW-Madison: materials design, machine learning, AI in engineering
– Tim McGee, Point Mass Technologies: robotics, extraterrestrial exploration (Dragonfly mission)
– Daniela Mitterberger, Princeton University: robotics in construction
– Marcus Mueller, Deutsches Zentrum fur Luft- und Raumfahrt (DLR), Germany: terrain segmentation, navigation in unstructured environments
– Robert Mueller, NASA Kennedy Space Center: advanced materials, lunar structures and construction (IPEx excavator)
– Adithya Pediredla, Dartmouth University: sensing, computer vision, non-line of sight sensing
– Benedict Rogers, University of Manchester: CFD, geomechanics, Smoothed Particle Hydrodynamics
– Aymeric Rousseau, Argonne National Lab: powertrain simulation
– Alex Schepelmann, NASA Glenn: terramechanics, robotics
– [keynote] Kenichi Soga, UC Berkeley: infrastructure sensing, energy geotechnics, ground engineering, soil and granular mechanics
– Andrew Spielberg, Carnegie Mellon University: robotics
– Paul van Susante, Michigan Tech: regolith, physical testing, excavation
– Rasmus Tamstorf, Intel: physics-based simulation, embodied AI
– Renato Vacondio, University of Parma: CFD, Smoothed Particle Hydrodynamics
– Frankie Zhu, Colorado School of Mines: dynamics and controls, robotics, machine learning, and space exploration.
Please consult this page for the latest updates, room information, changes in schedule, etc.
September 9, 2025: Tutorials highlighting the use of Project Chrono
As part of MaGIC 2025, the tutorial will provide instruction on Project Chrono, an open-source multi-physics simulation framework. The program consists of seven hands-on tutorial sessions covering subjects such as terramechanics, distributed co-simulation, construction processes, and sensor simulation. These sessions will demonstrate Chrono functionalities applicable to vehicle-terrain interaction and the design of autonomous systems. Participants will work with practical examples and have access to technical guidance. Please be advised that the tutorial content is tentative, and a finalized schedule will be released soon.
Overview of the tutorial sessions
Chrono DEM Solver
Introduction to Chrono’s GPU-based Discrete Element Method (DEM) solver for simulating granular materials. We will show an example of granular material application with heat transfer phenomena. We will walk through a 3D demo first, and then a hands-on 2D exercise.
Duration: 2 hours
Chrono FSI framework for fluid solid interaction
Introduction to the Fluid Solid Interaction framework in Chrono that allows simulating interaction between mechanisms containing Rigid and Flexible bodies with water and granular material. We will go through the basics of how the framework is setup and how information is exchanged between different parts of Chrono. We will then show two examples that leverage the framework:
- A Polaris RZR with deformable tires moving over a pontoon floating on water simulated through FSI’s coupling with Chrono’s fluid solver;
- A Polaris RZR with deformable tires moving over deformable terrain simulated through FSI’s coupling with CRM. The examples will not be coded live but will be setup to run directly on the participants machines.
Duration: 2 hours
Chrono CRM, high-fidelity terramechanics model
Introduction to a Chrono terramechanics model that regards the terrain as a continuum, instead of treating it as a collection of fine particles/elements. Chrono’s Continuum Representation Model (CRM) is physics-based, runs fast, and produces accurate results. We will cover the theory and the numerical method behind Chrono CRM and then walk through a demonstration of setting up a drawbar pull test with a full scale rover. The walk-through will be hands-on where we will live code the simulation setup, build it, run it, and visualize the results.
Duration: 2.5 hours
Synchrono, distributed co-simulation capabilities
Synchrono is a high-performance co-simulation framework that enables scalable, distributed simulation of robotic, vehicular, and infrastructure systems. It allows multiple Chrono-based simulation nodes—each representing a subsystem like a vehicle, sensor, or infrastructure component—to run concurrently on different processes or machines while maintaining synchronized state. In this session, we will cover the architecture of Chrono::Synchrono, the message-passing system, the data-distribution system used for inter-node communication, and how the framework supports modular simulation design across multiple computing nodes. We will then explore two example scenarios:
- Multiple autonomous vehicles driving as a convoy, with each vehicle simulated as an independent agent using its sensors and control logic.
- Multiple rovers traversing on SCM deformable terrain.
Duration: 1 hour.
Using Chrono for Construction Autonomy Design
- Application 1: rigid body bulldozing (remove rock or box from a field).
- Application 2: soil leveling autonomy design.
Chrono Robotics and ROS Interface.
- Application 1: ART vehicle with sensors.
- Application 2: Apartment environment explore.
Chrono::Sensor for software-in-the-loop (SITL) development
Chrono::Sensor is a framework that simulates common sensors (i.e., camera, IMU, GPS, LiDAR) operating in Chrono virtual worlds. This allows for fast software-in-the-loop development of robotic and ground vehicle systems. We will begin with an introduction to the Chrono::Sensor API and implementation (manager, sensor filters). We will then learn to integrate the built in GPS, IMU, Camera and LiDAR models into a Chrono::Vehicle simulation. We will then briefly cover how to extend this system for SITL using Chrono::ROS integration and simulating a robot using an Extended Kalman Filter for perception. Finally, we cover camera models available and their use cases.