Kirk MacTavish

University of Toronto

Papers

9

Total Citations

229

H-Index

9

About

Kirk MacTavish is a leading researcher in long-term autonomous navigation, specializing in vision-based localization and simultaneous localization and mapping (SLAM) for mobile robots operating in challenging, GPS-denied environments. His most influential work centers on the "Visual Teach and Repeat" (VT&R) paradigm, where robots autonomously retrace manually taught routes over vast distances using only inexpensive cameras. MacTavish’s 2016 paper, "Bridging the appearance gap," with 82 citations, introduced multi-experience localization to overcome environmental changes from lighting and weather, a critical breakthrough for persistent outdoor autonomy. He further advanced this with VT&R 2.0, demonstrated in a 2017 field test covering miles of rugged terrain. Beyond wheeled robots, MacTavish pioneered tethered SLAM (TSLAM) for steep, dangerous terrains, and relative continuous-time SLAM for rolling-shutter cameras. His work on night-time visual odometry using headlights and colour-constant image place recognition showcases his ability to solve real-world perception challenges. With over 200 total citations across his top papers, MacTavish’s contributions have expanded the practical limits of vision-based navigation, enabling robust, long-term autonomy for field robotics.

Research Focus

Key Achievements

9
H-Index
9
Papers
229
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
Bridging the appearance gap: Multi-experience localization for long-term visual teach and repeat
82 citations · 2016
📈 Most Prolific Year: 2016 (4 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of Toronto

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
    Relative continuous-time SLAM
    18 citations · 2015
  6. 6
  7. 7
  8. 8
  9. 9

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago