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INSTRUCTORS:
Kris Zacny
Sarah Lam
Nicolas Bolatto
Waylon Lee
Course Length: 1 hour
Purpose and Background
These presentations were recorded at Earth and Space 2026 Conference.
Rover Progress for the 2028 Lunar-Vise Mission to Gruithuisen Domes (16 minutes)
This presentation provides an overview of the rover being developed for the 2028 Lunar-VISE mission to the Gruithuisen Domes region of the Moon. The rover is designed to support scientific investigations of unusual volcanic formations that may reveal insights into the Moon's geologic history. The speaker discusses Honeybee Robotics' modular rover architecture, which enables a common technology platform across multiple lunar missions. Key rover capabilities include autonomous navigation, direct-to-Earth communication, scientific payload integration, and long-distance surface traverses. The presentation also highlights the rover's deployment mechanism, mobility testing, wheel design, and operational concepts for collecting mineralogical and volatile measurements. The mission demonstrates how medium-sized robotic explorers can deliver significant scientific return while maintaining lower cost and greater deployment flexibility than larger rover systems.
Design of a High Mobility Rover & Concepts of Operation (16 minutes)
This presentation explores the development of a highly mobile planetary rover capable of traversing challenging extraterrestrial terrain. The speaker reviews the strengths and limitations of traditional wheeled rovers, legged robots, and hybrid wheel-leg systems. A research platform known as the Rad Exploration Vehicle (RAV) is introduced as a testbed for active suspension technologies and advanced mobility concepts. The rover incorporates force sensing, active suspension control, chassis leveling, and adaptive traction management to improve mobility on soft soils and steep slopes. Concepts of operation include terrain detection, obstacle negotiation, payload stabilization, and tip-over prevention. The work aims to improve rover adaptability and operational safety in future lunar and Martian exploration missions.
Group Planning for Autonomous Robot Swarms Conducting Lunar Regolith-Shifting Operations (14 minutes)
This presentation examines how teams of autonomous robots can collaborate to perform lunar site preparation and regolith-moving operations. The research investigates whether multiple smaller robots can outperform a single large excavation vehicle when total system mass is constrained. A simulation framework is presented that models terrain modification, excavation, hauling, and deposition activities across a lunar worksite. The study explores decentralized decision-making approaches that allow large groups of robots to operate without centralized control. Researchers evaluate how communication, task allocation, sensing range, and rover specialization affect overall system productivity. The work contributes to future lunar construction concepts involving landing pads, roads, berms, and infrastructure development.
Crater Detection Neural Network Training Using High-Fidelity 3D Terrain Rendering (13 minutes)
This presentation investigates the use of high-fidelity simulated lunar terrain data for training artificial intelligence systems that detect craters for navigation and landing applications. The study utilizes Space Teams Pro and Unreal Engine-based terrain simulations to generate realistic lunar imagery under operational lighting conditions. Researchers compare two machine learning approaches—Mask R-CNN and YOLO—for automated crater detection and localization. Thousands of simulated images are used to train and validate neural network models before evaluating their performance on actual lunar reconnaissance imagery. Results demonstrate that synthetic datasets can effectively support AI training while reducing dependence on real mission imagery. The work supports future autonomous landing systems and crater-based navigation technologies for lunar exploration.
Benefits and Learning Outcomes
Upon completion of this course, you will be able to:
- Explain the design features, mission objectives, and operational capabilities of the Lunar-VISE rover planned for exploration of the Gruithuisen Domes.
- Describe how active suspension systems and force sensing technologies improve rover mobility and stability on planetary terrain.
- Discuss how autonomous multi-robot systems can be used to perform large-scale lunar site preparation and regolith manipulation tasks.
- Identify how synthetic terrain rendering and machine learning algorithms can be used to improve crater detection for lunar navigation and landing systems.
Assessment of Learning Outcomes
Students' achievement of the learning outcomes will be assessed via a short post-test assessment (true-false, multiple choice, and/or fill in the blank questions).
Who Should Attend?
- Aerospace / Space Systems Engineers
- Civil Engineers (Geotechnical, Structural, Construction)
- Geotechnical / Materials Engineers
- Robotics & Autonomous Systems Engineers
- Researchers & Academics
- Government & Space Agency Professionals
How to Earn your CEUs/PDHs and Receive Your Certificate of Completion
To receive your certificate of completion, you will need to complete a short on-line post-test and receive a passing score of 70% or higher within 365 days of the course purchase.
How do I convert CEUs to PDHs?
1.0 CEU = 10 PDHs [Example: 0.1 CEU = 1 PDH]