Papers

5

Total Citations

57

H-Index

4

About

Alexandre Albore is a leading researcher in robotics and artificial intelligence, specializing in dependable autonomous systems, planning under uncertainty, and skill-based robotic architectures. His work addresses the critical challenge of enabling robots to act reliably in partially observable and dynamic environments, where achieving goals may not always be guaranteed. Albore’s most influential contribution is his 2022 paper on “Skill-based design of dependable robotic architectures,” which has garnered 23 citations and provides a foundational framework for building robust, modular robotic systems. He also introduced the AMPLE framework (2018), an anytime planning and execution system that tackles real-time decision-making in uncertain robotic contexts, earning 10 citations. His earlier research on action selection for planning with sensing (2007) and acting in partially observable environments with dead-end states (2015) has been widely recognized for advancing theoretical understanding of belief-space planning. Most recently, Albore has extended his expertise to space applications, co-authoring a 2025 study on automated construction of modular space platforms. With a career spanning over two decades, his work bridges theory and practice, making him a key figure in the development of intelligent, resilient robotic systems for complex, real-world tasks.

Research Focus

Key Achievements

4
H-Index
5
Papers
57
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Skill-based design of dependable robotic architectures
23 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Université Fédérale de Toulouse Midi-Pyrénées, Pompeu Fabra University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago