activity
20172026
most citedLearning Efficient Policies for Picking Entangled Wire Harnesses: An Approach to Industrial Bin Picking

41 citations · 104 across the 35 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CV2023

NeuralLabeling: A versatile toolset for labeling vision datasets using Neural Radiance Fields

Floris Erich, Naoya Chiba, Yusuke Yoshiyasu +3

We present NeuralLabeling, a labeling approach and toolset for annotating 3D scenes using either bounding boxes or meshes and generating segmentation masks, affordance maps, 2D bou…

cs.RO2023★ 7 cited

Motion Priority Optimization Framework towards Automated and Teleoperated Robot Cooperation in Industrial Recovery Scenarios

Shunki Itadera, Yukiyasu Domae

In this study, we introduce an optimization framework aimed at enhancing the efficiency of motion priority design in scenarios involving automated and teleoperated robots within an…

cs.RO2023★ 1 cited

A Closed-Loop Bin Picking System for Entangled Wire Harnesses using Bimanual and Dynamic Manipulation

Xinyi Zhang, Yukiyasu Domae, Weiwei Wan +1

This paper addresses the challenge of industrial bin picking using entangled wire harnesses. Wire harnesses are essential in manufacturing but poses challenges in automation due to…

cs.RO2023

Force Map: Learning to Predict Contact Force Distribution from Vision

Ryo Hanai, Yukiyasu Domae, Ixchel G. Ramirez-Alpizar +2

When humans see a scene, they can roughly imagine the forces applied to objects based on their experience and use them to handle the objects properly. This paper considers transfer…

cs.RO2023★ 8 cited

Learning to Dexterously Pick or Separate Tangled-Prone Objects for Industrial Bin Picking

Xinyi Zhang, Yukiyasu Domae, Weiwei Wan +1

Industrial bin picking for tangled-prone objects requires the robot to either pick up untangled objects or perform separation manipulation when the bin contains no isolated objects…