Dr. Vittorio FRANZESE is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg's SPASYS department. His work focuses on CubeSat technology, autonomous space systems, and deep-space exploration. He leads projects like the POQUITO PocketQube mission and the LUMIO lunar CubeSat, aiming to advance miniaturized satellite capabilities for interplanetary navigation and meteoroid impact monitoring. Key research areas include spacecraft autonomy, optical navigation algorithms, and mission design for CubeSats. He has contributed to initiatives such as the ERC-funded EXTREMA project, developing self-driving interplanetary CubeSats. His technical expertise spans satellite systems engineering, trajectory optimization, and sensor development for space applications. Publications highlight advancements in laser communication terminals, asteroid mission analysis, and swarm satellite technologies. Collaborative efforts include the Hera Milani CubeSat mission for asteroid exploration. His work bridges theoretical research with practical implementation, emphasizing innovation in low-cost space technologies.
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Dr. Carol Martinez Luna is a Research Scientist and Deputy Head of the Space Robotics group (SpaceR) at the SnT Interdisciplinary Centre, University of Luxembourg. She holds a PhD in Robotics and Automation from Universidad Politécnica de Madrid (2013) and previously served as an Assistant Professor at Pontificia Universidad Javeriana, Colombia. Her research spans Space Robotics , Computer Vision , and Machine Learning , with current focus areas including: Multi-purpose manipulation for planetary/orbital robots Perception systems for autonomous space operations Domain adaptation to bridge simulation-to-reality gaps On-ground testing of orbital technologies Recent publications (2022-2025) predominantly address space debris removal , autonomous grasping , and robotic perception , with heavy emphasis on machine learning techniques and high-fidelity simulation validation. Notable trends include generative models for manipulation and adaptive control under uncertainty. She actively advises 7 PhD students and 9 Master's candidates on topics ranging from space manipulation to vision-based safety systems. Her lab develops experimental platforms for orbital scenario emulation and collaborates on ESA-funded debris removal initiatives.
- Space Robotics
- Computer Vision
- Machine Learning
- +۵ مورد دیگر
Dr. Mohammadamin ALANDIHALLAJ is a Postdoctoral Researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), within the SPASYS department. His work focuses on advanced space systems engineering, control systems, and aerospace technologies. Key research areas include satellite mission design (e.g., the POQUITO PocketQube mission), autonomous orbital correction using machine learning, and fractionated spacecraft architectures for enhanced connectivity. His research integrates cutting-edge techniques like Model Predictive Control (MPC), reinforcement learning (e.g., PPO algorithms), and LSTM networks to address challenges in spacecraft navigation, fault tolerance, and on-orbit operations. Notable contributions include developing control strategies for satellite docking, fuel-efficient orbit correction, and mitigating disturbances in on-orbit refueling. Dr. ALANDIHALLAJ also leads the Zero-G Lab, a multi-purpose facility for simulating space operations, enabling experimental validation of technologies such as floating platform stabilization and fuel sloshing mitigation. His work bridges theoretical advancements with practical applications, including wildfire monitoring via fractionated spacecraft and deep-space exploration systems for Europa missions. He has authored over 30 peer-reviewed publications, with recent emphasis on AI-driven space systems, fractionated architectures, and zero-gravity environment emulation. Current research trends highlight the convergence of machine learning, systems engineering, and experimental validation for next-generation space technologies. Awards and recognitions are not explicitly mentioned in the provided texts. His research is supported by collaborations within SnT and interdisciplinary projects at the University of Luxembourg.
Holger Voos is Full Professor in Engineering Science at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), where he leads the Automatic Control Laboratory. His research focuses on distributed networked control, autonomous robotic systems, safety-critical applications, and mechatronic system design. His recent publications demonstrate strong research emphasis on: Advanced SLAM algorithms integrating visual, inertial and wireless technologies Optimal control strategies for spacecraft formations and aerial robots Neuromorphic vision systems and sensor fusion techniques Reinforcement learning approaches for robotic manipulation Constraint-based optimization methods for robotic perception and control
Arunkumar RATHINAM is a Postdoctoral researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the CVI2 department. His research focuses on autonomous systems, spacecraft navigation, and machine learning applications in space exploration. He has contributed to the development of datasets like SPARK and Zero-G Lab, which advance space operations emulation and computer vision techniques. Affiliations: SnT-CVI2, University of Luxembourg Key Research Areas: spacecraft pose estimation, thermal anomaly detection, autonomous navigation, and robotics for space missions His work bridges machine learning with practical space systems, addressing challenges in thermal monitoring (e.g., Li-ion battery cells) and vision-based navigation for spacecraft proximity operations. He has pioneered experimental facilities like the Zero-G Lab to simulate microgravity environments and test space robotics systems. Notable contributions include datasets such as SPARK and AKM, which provide critical data for training models in spacecraft trajectory estimation and textureless target detection. His publications emphasize real-world applications of AI in space systems, including RGB-T pedestrian detection and hybrid attention mechanisms for robust vision systems.