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Jun Takahashi

4 accepted papers

2026

Learning From Planned Data to Improve Robotic Pick-and-Place Planning Efficiency

RA-L 2026

This work proposes a learning method to accelerate robotic pick-and-place planning by predicting shared grasps. Shared grasps are defined as grasp poses feasible to both the initial and goal object configurations in a pick-and-place task. Traditional analytical methods for solving shared grasps eval

Cited by 2Source ↗Scholar ↗
2026

Learning from Planned Data to Improve Robotic Pick-And-Place Planning Efficiency

ICRA 2026poster

This work proposes a learning method to accelerate robotic pick-and-place planning by predicting shared grasps. Shared grasps are defined as grasp poses feasible to both the initial and goal object configurations in a pick-and-place task. Traditional analytical methods for solving shared grasps eval…

2026

Zero-Shot Recognition of Test Tube Types by Automatically Collecting and Labeling RGB Data

ICRA 2026poster

This work presents a method for automatically detecting and recognizing test tube types in a rack. It leverages automatic segmentation, clustering, and labeling processes to eliminate the need for explicitly preparing training data. These processes are addressed by using combined global prediction a…

Cited by 0Source ↗Scholar ↗
2025

Zero-Shot Recognition of Test Tube Types by Automatically Collecting and Labeling RGB Data

RA-L 2025

This work presents a method for automatically detecting and recognizing test tube types in a rack. It leverages automatic segmentation, clustering, and labeling processes to eliminate the need for explicitly preparing training data. These processes are addressed by using combined global prediction a

Cited by 0Source ↗Scholar ↗