About

Torea Foissotte is a roboticist whose research centers on autonomous manipulation and perception for humanoid robots, with a particular emphasis on dual-arm coordination, 3D object modeling, and error recovery. Her most influential work, "Pick and place planning for dual-arm manipulators" (2012, 47 citations), introduced a two-phase planning method that enables robots to efficiently grasp and transfer objects using both arms—a foundational contribution to dexterous manipulation. She also advanced autonomous 3D modeling through a series of papers (2008–2010, totaling over 50 citations) that developed next-best-view algorithms, allowing humanoid robots to actively explore and build visual models of unknown objects by coupling computer vision with whole-body posture generation. Her work on "Error recovery using task stratification and error classification" (2013, 28 citations) further enhanced robotic robustness by decomposing manipulation tasks into skills and enabling systematic error handling. Foissotte’s research bridges perception, planning, and control, with her combined work accumulating over 150 citations. Her contributions are particularly notable for addressing the unique constraints of humanoid platforms, such as limited sensors and complex kinematics, making autonomous object manipulation and modeling more reliable in real-world environments.

Research Focus

Key Achievements

6
H-Index
8
Papers
160
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
Pick and place planning for dual-arm manipulators
47 citations · 2012
📈 Most Prolific Year: 2009 (3 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Systems Research Institute, National Institute of Advanced Industrial Science and Technology, Centre National de la Recherche Scientifique

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago