Jonathan D. Gammell

University of Toronto, University of Oxford, Oxford Research Group, Science Oxford, Robotics Research (United States), Queen's University

Papers

21

Total Citations

823

H-Index

9

About

No biography available yet.

Research Focus

Computer science19 · 820 citations
Artificial intelligence17 · 729 citations
Computer vision11 · 688 citations
Sampling (signal processing)4 · 579 citations
Algorithm6 · 548 citations
Theoretical computer science4 · 518 citations
Graph3 · 511 citations
Bit (key)2 · 504 citations
Random graph1 · 417 citations
Robot12 · 259 citations
Mathematics8 · 162 citations
Motion (physics)4 · 127 citations

Key Achievements

9
H-Index
21
Papers
823
Total Citations
39
Avg Citations/Paper
🏆 Most Cited Paper
Batch Informed Trees (BIT*): Sampling-based Optimal Planning via the Heuristically Guided Search of Implicit Random Geometric Graphs
417 citations · 2015
📈 Most Prolific Year: 2020 (3 Papers)
🤝 Key Collaborators: 80
🏛 Institutions: University of Toronto, University of Oxford, Oxford Research Group, Science Oxford, Robotics Research (United States), Queen's University

Top Papers

  1. 1
    Batch Informed Trees (BIT*): Sampling-based Optimal Planning via the Heuristically Guided Search of Implicit Random Geometric Graphs
    417 citations · 2015
  2. 2
    Advanced BIT* (ABIT*): sampling-based planning with advanced graph-search techniques
    87 citations · 2020
  3. 3
    Adaptively Informed Trees (AIT*) and Effort Informed Trees (EIT*): Asymmetric bidirectional sampling-based path planning
    70 citations · 2022
  4. 4
    Multimotion Visual Odometry (MVO): Simultaneous Estimation of Camera and Third-Party Motions
    61 citations · 2018
  5. 5
    The Oxford Multimotion Dataset: Multiple SE(3) Motions With Ground Truth
    42 citations · 2019
  6. 6
    Surface Edge Explorer (see): Planning Next Best Views Directly from 3D Observations
    38 citations · 2018
  7. 7
    Into Darkness: Visual Navigation Based on a Lidar-Intensity-Image Pipeline
    34 citations · 2016
  8. 8
    Task and Motion Informed Trees (TMIT*): Almost-Surely Asymptotically Optimal Integrated Task and Motion Planning
    19 citations · 2022
  9. 9
    The surface edge explorer (SEE): A measurement-direct approach to next best view planning
    11 citations · 2024
  10. 10
    Effort Informed Roadmaps (EIRM*): Efficient Asymptotically Optimal Multiquery Planning by Actively Reusing Validation Effort
    7 citations · 2023

Key Collaborators

MPMarlin P. Strub5 shared papersTDTimothy D. Barfoot5 shared papersSMStephen Mellon4 shared papersCMColin McManus4 shared papersIYIrene Yang4 shared papersPFPaul Furgale4 shared papersDWDavid W. Murray4 shared papersCHChi Hay Tong3 shared papersKMKevin M. Judd2 shared papersMRMark R. Beauchamp2 shared papersJEJohn Enright2 shared papersSASean Anderson2 shared papersEMEmily McCullough2 shared papersEBErik Beerepoot2 shared papersKLK. Leung2 shared papersMGM. G. Daly2 shared papersRBRowan Border2 shared papersGRG. R. Osinski2 shared papersHDH. Dong2 shared papersPJPiotr Jasiobedzki2 shared papers
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