Lucas Manuelli

Massachusetts Institute of Technology, Nvidia (United Kingdom), Vassar College

Papers

14

Total Citations

904

H-Index

11

About

No biography available yet.

Research Focus

Artificial intelligence14 · 904 citations
Computer science14 · 904 citations
Computer vision9 · 708 citations
Object (grammar)8 · 646 citations
Task (project management)9 · 630 citations
Robot8 · 504 citations
Human–computer interaction7 · 435 citations
Representation (politics)4 · 421 citations
Segmentation4 · 348 citations
Leverage (statistics)4 · 348 citations
Pipeline (software)4 · 348 citations
Variety (cybernetics)4 · 298 citations

Key Achievements

11
H-Index
14
Papers
904
Total Citations
65
Avg Citations/Paper
🏆 Most Cited Paper
KPAM: KeyPoint Affordances for Category-Level Robotic Manipulation
170 citations · 2022
📈 Most Prolific Year: 2018 (4 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: Massachusetts Institute of Technology, Nvidia (United Kingdom), Vassar College

Top Papers

  1. 1
    KPAM: KeyPoint Affordances for Category-Level Robotic Manipulation
    170 citations · 2022
  2. 2
    Label Fusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes
    113 citations · 2018
  3. 3
    Localizing external contact using proprioceptive sensors: The Contact Particle Filter
    101 citations · 2016
  4. 4
    Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation
    100 citations · 2018
  5. 5
    CLIPort: What and Where Pathways for Robotic Manipulation
    99 citations · 2021
  6. 6
    Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation
    95 citations · 2018
  7. 7
    kPAM: KeyPoint Affordances for Category-Level Robotic Manipulation
    56 citations · 2019
  8. 8
    Director: A User Interface Designed for Robot Operation with Shared Autonomy
    49 citations · 2016
  9. 9
    Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulation
    48 citations · 2022
  10. 10
    Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning
    35 citations · 2020

Key Collaborators

RTRuss Tedrake11 shared papersPFPete Florence8 shared papersPMPat Marion4 shared papersDFDieter Fox3 shared papersMSMohit Shridhar2 shared papersSKScott Kuindersma2 shared papersTKTwan Koolen2 shared papersGIGreg Izatt2 shared papersMFMaurice Fallon2 shared papersCPClaudia Pérez D’Arpino2 shared papersAVAndrés Valenzuela2 shared papersRDRobin Deits2 shared papersHDHongkai Dai2 shared papersMAMatt Antone2 shared papersWGWei Gao1 shared papersWGWei Gao1 shared papersMSM.H Shridhar1 shared papersYLYunzhu Li1 shared papersYLYunzhu Li1 shared papersJCJohn Carter1 shared papers
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