Lorenzo Capra
Papers
2
Total Citations
15
H-Index
2
About
Lorenzo Capra is a researcher at the forefront of space robotics and artificial intelligence, with a primary focus on autonomous guidance for in-orbit servicing (IOS). His major contribution lies in developing a novel guidance algorithm for redundant space manipulators using deep reinforcement learning (DRL), a breakthrough that addresses the critical challenge of space debris threatening operational satellites and future missions. This work, published in 2024, has already garnered 11 citations, underscoring its immediate impact on the field. Capra’s research enhances the autonomy of robotic systems, enabling them to perform complex tasks like satellite repair and debris removal without direct human control—a key priority for space agencies worldwide. By integrating DRL with manipulator kinematics, he has advanced the safety and efficiency of autonomous operations in the hazardous space environment. His notable achievement includes demonstrating how AI-driven guidance can optimize manipulator redundancy, paving the way for more resilient and cost-effective space missions. Capra’s work is essential reading for students and researchers interested in the convergence of robotics, reinforcement learning, and space exploration, offering a practical pathway toward sustainable orbital operations.
Research Focus
Key Achievements
Top Papers
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- 2