Daniele Magazzeni
Papers
12
Total Citations
723
H-Index
10
About
Daniele Magazzeni is a leading researcher at the intersection of artificial intelligence and robotics, whose work has fundamentally advanced how robots reason, plan, and interact with humans. His primary research areas include automated task and motion planning, human-robot interaction, and explainable AI for robotics. Magazzeni is best known for developing **ROSPlan**, a groundbreaking framework that integrates AI planning into the Robot Operating System (ROS), enabling robots to autonomously combine basic capabilities like navigation and manipulation to achieve high-level goals. This work, published in 2015, has garnered over 220 citations and become a standard tool in the robotics community. His contributions extend to probabilistic planning for situated robots and temporal reasoning for complex logistics tasks, with his 2014 ICRA paper accumulating over 250 citations. More recently, Magazzeni has pioneered research on explainable robotics, developing methods to help robots articulate why they chose a particular path or plan—a critical step toward trustworthy autonomous systems. His work on providing explanations for motion planning and path plan optimality has opened new avenues for transparent human-robot collaboration, making him a key figure in shaping the future of intelligent, accountable robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Proceedings of IEEE International Conference on Robotics and Automation (ICRA 2014)252 citations · 2014
- 2ROSPlan: Planning in the Robot Operating System223 citations · 2015
- 3Automated Planning for Robotics81 citations · 2019
- 4Probabilistic Planning for Robotics with ROSPlan31 citations · 2019
- 5
- 6Towards providing explanations for robot motion planning22 citations · 2021
- 7Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics (ICINCO-11)20 citations · 2011
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- 9
- 10Replanning for Situated Robots13 citations · 2019