Quadrupeds for Planetary Exploration: Field Testing Control Algorithms on an Active Volcano

2025-10-21

AI Summary

Planetary terrains—such as surface fissures and boulder-strewn fields—pose significant traversal challenges for wheeled rovers. Method: This study proposes an adaptive optimal control framework for quadrupedal robots designed for lunar and Martian exploration, integrating state estimation, dynamic gait planning, and a modular software architecture. Field experiments were conducted on unstructured volcanic terrain at Vulcano Island, Italy, demonstrating autonomous gap crossing and robust locomotion over highly irregular surfaces. Contribution/Results: To our knowledge, this is the first systematic application of adaptive optimal control algorithms for legged robots in a high-fidelity analog extraterrestrial environment. The framework demonstrates robustness and adaptability across loose scree, steep slopes, and elevated-temperature zones. Experimental results confirm a substantial expansion of traversability boundaries for planetary surface mobile robots, providing an engineering-ready technical foundation for future interplanetary legged exploration missions.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search

Abstract

Missions such as the Ingenuity helicopter have shown the advantages of using novel locomotion modes to increase the scientific return of planetary exploration missions. Legged robots can further expand the reach and capability of future planetary missions by traversing more difficult terrain than wheeled rovers, such as jumping over cracks on the ground or traversing rugged terrain with boulders. To develop and test algorithms for using quadruped robots, the AAPLE project was carried out at DFKI. As part of the project, we conducted a series of field experiments on the Volcano on the Aeolian island of Vulcano, an active stratovolcano near Sicily, Italy. The experiments focused on validating newly developed state-of-the-art adaptive optimal control algorithms for quadrupedal locomotion in a high-fidelity analog environment for Lunar and Martian surfaces. This paper presents the technical approach, test plan, software architecture, field deployment strategy, and evaluation results from the Vulcano campaign.

Problem

• Testing quadruped robot control algorithms on active volcanoes
• Developing adaptive locomotion for challenging planetary terrains
• Validating legged robot performance in analog lunar environments

Innovation

• Quadruped robots tested on active volcano
• Adaptive optimal control algorithms for locomotion
• High-fidelity analog environment for planetary surfaces