Papers

12

Total Citations

963

H-Index

9

About

Lorenzo Riano is a pioneering researcher in robotics whose work bridges the gap between high-level task planning and natural human-robot interaction. His primary research areas include combined task and motion planning, human-robot interaction through spatial language grounding, and haptic learning. Riano's most impactful contribution is his 2014 paper on combined task and motion planning (474 citations), which introduced an extensible, planner-independent interface layer that allows off-the-shelf task planners to work seamlessly with motion planning algorithms—a breakthrough that eliminated the need for specialized integrated systems. He also made significant strides in grounding spatial relations for human-robot interaction (146 citations), enabling robots to understand spatial prepositions and execute commands based on visual percepts. Riano's work on haptic adjectives (145 and 107 citations) is particularly notable, as he developed methods for robots to learn the meaning of tactile descriptors through physical interaction, advancing the field of robotic language acquisition. His research has been applied to the PR2 robot and has implications for telepresence and autonomous navigation, demonstrating his commitment to creating robots that can communicate naturally with humans.

Research Focus

Key Achievements

9
H-Index
12
Papers
963
Total Citations
80
Avg Citations/Paper
🏆 Most Cited Paper
Combined task and motion planning through an extensible planner-independent interface layer
474 citations · 2014
📈 Most Prolific Year: 2013 (3 Papers)
🤝 Key Collaborators: 35
🏛 Institutions: University of California, Berkeley, University of Ulster, University of Palermo

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago