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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 2SourceScholar
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 0SourceScholar
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 0SourceScholar