Takuto Watanabe

Meiji University

Papers

2

Total Citations

47

H-Index

2

About

Takuto Watanabe is a robotics researcher specializing in vision-based autonomous navigation, with a particular focus on enabling robots to operate intelligently in human-centric environments using minimal, cost-effective sensors. His primary research areas include semantic segmentation for visual navigation, monocular camera-based perception, and intersection detection for mobile robot path planning. Watanabe’s most influential work, “Visual Navigation Based on Semantic Segmentation Using Only a Monocular Camera as an External Sensor” (2020, 38 citations), challenges the field’s reliance on expensive 3D LiDAR by demonstrating that a single camera can provide sufficient environmental understanding for autonomous movement. This contribution is significant for making robotics more accessible and practical for everyday settings. Additionally, his feasibility study on intersection detection from a single-shot image (2021, 9 citations) advances robot navigation in complex urban-like environments. By reducing hardware requirements without sacrificing performance, Watanabe’s research paves the way for affordable, visually-guided robots that can safely coexist with humans.

Research Focus

Key Achievements

2
H-Index
2
Papers
47
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Visual Navigation Based on Semantic Segmentation Using Only a Monocular Camera as an External Sensor
38 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Meiji University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago