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Origami-inspired deployable structures for space exploration: Integrating artificial intelligence, robotics, and advanced materials
Conference paper

Origami-inspired deployable structures for space exploration: Integrating artificial intelligence, robotics, and advanced materials

Nijanthan Vasudevan, Oudayl Massat, Arjuna Karthikeyan Senthilvel Kavitha and Padmapriya Sampathkumar
IAF Materials and Structures Symposium - Held at the 76th International Astronautical Congress, IAC 2025, pp 601-614
2025
DOI: https://doi.org/10.52202/083088-0067

Abstract

Autonomous deployment Deployable mechanisms Evolutionary generative design multi-objective genetic algorithms Origami-inspired structures Shape-memory alloys
Next-generation space exploration requires deployable structures that are lightweight, compact, and resilient under harsh orbital and planetary conditions. This paper proposes a conceptual framework for origami-inspired deployable systems, merging insights from Artificial Intelligence (AI), Robotics, and advanced materials research. By incorporating folding techniques such as Miura-ori and Yoshimura tessellations, this approach aims to significantly reduce stowage volume and mass while preserving structural integrity during deployment. Central to this framework is finite element analysis (FEA), used to investigate stress distribution, deformation, and dynamic responses under launch vibrations, microgravity, and extreme temperature fluctuations. Carbon fiber-reinforced polymers and shape-memory alloys (SMAs) serve as primary materials, chosen for their superior strength-to-weight ratios, adaptability, and radiation resistance. An evolutionary generative design methodology—employing multi-objective genetic algorithms with parametric constraints for mechanical properties and fold patterns—optimizes deployment strategies by iteratively balancing mass efficiency, rigidity, and reliability. The system also integrates robotic platforms equipped with precision actuators, sensors, and kinematic models rooted in rigid body and multi-body dynamics. These autonomous robots govern real-time folding and unfolding operations, adapting to anomalies such as unexpected oscillations or partial misalignments. Structural health monitoring is achieved using embedded sensor networks, including fiber-optic arrays, which enable continuous measurements of stress, strain, and temperature. Advanced analytics—covering predictive maintenance algorithms and anomaly detection—preempt potential material fatigue or mechanical failures, thereby minimizing downtime and extending operational lifespans. Methodologically, nonlinear dynamics, control theory, and multi-objective optimization form the theoretical underpinning, ensuring robust performance under evolving mission constraints. Scaled prototypes will be tested in vacuum chambers, radiation test beds, and wide temperature extremes to validate overall feasibility. Expected outcomes include higher deployment accuracy, reduced mass budgets, and improved reusability compared to conventional deployable systems. Future research will delve into electroactive polymers, 4D printing, and the scaling of these origami-inspired designs for large-scale applications, from space habitats to expansive solar sails. By fusing origami engineering, robotic autonomy, and innovative material science, this framework offers a pioneering avenue for developing adaptable, resilient, and highly efficient space structures.

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