• Sakshi Divedi
• Asst. Prof. Needhumol M. Pillai

Robotic systems are used in space exploration missions to carry out crucial tasks in harsh environments. However, these robots are susceptible to structural damage from radiation, micrometeorite impacts, and mechanical stress. Traditional maintenance methods are costly and impractical for deep-space missions. This research explores the integration of Artificial Intelligence (AI) and self-healing materials to develop autonomous space robots capable of detecting, assessing, and repairing damage without human intervention. Machine learning and sensor data will be used by AI-powered damage detection systems to quickly identify material fatigue. Self-healing materials like nanomaterial-based coatings, shape memory alloys, and self-healing polymers will allow for autonomous structural integrity restoration. By reducing the need for human-led repairs, the study aims to increase the longevity, dependability, and cost-effectiveness of space robotics. AI models that are optimized for low-energy processing and self-healing materials that are more durable in extreme space conditions will be the primary areas of future research.

Artificial Intelligence, SelfHealing Materials, Autonomous Space Robots, AI-Based Fault Detection, Predictive Maintenance, Machine Learning, Space Exploration, Structural Integrity, Smart Materials, Reinforcement Learning

"AI-Driven Self-Healing Space Robots: Integrating Autonomous Damage Detection and Repair Mechanis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.g310-g314, March-2025, Available :http://www.jetir.org/papers/JETIR2503635.pdf

"AI-Driven Self-Healing Space Robots: Integrating Autonomous Damage Detection and Repair Mechanis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppg310-g314, March-2025, Available at : http://www.jetir.org/papers/JETIR2503635.pdf