activity
20162020
most citedInitial Experiments on Learning-Based Randomized Bin-Picking Allowing Finger Contact with Neighboring Objects

3 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

cs.RO20201 cited

Development of a Shape-memorable Adaptive Pin Array Fixture

Peihao Shi, Zhengtao Hu, Kazuyuki Nagata +3

This paper proposes an adaptive pin-array fixture. The key idea of this research is to use the shape-memorable mechanism of pin array to fix multiple different shaped parts with co…

cs.RO2020

Functionally Divided Manipulation Synergy for Controlling Multi-fingered Hands

Kazuki Higashi, Keisuke Koyama, Ryuta Ozawa +3

Synergy supplies a practical approach for expressing various postures of a multi-fingered hand. However, a conventional synergy defined for reproducing grasping postures cannot per…

cs.RO2018

Tool Exchangeable Grasp/Assembly Planner

Kensuke Harada, Kento Nakayama, Weiwei Wan +3

This paper proposes a novel assembly planner for a manipulator which can simultaneously plan assembly sequence, robot motion, grasping configuration, and exchange of grippers. Our…

cs.RO2018

Experiments on Learning Based Industrial Bin-picking with Iterative Visual Recognition

Kensuke Harada, Weiwei Wan, Tokuo Tsuji +3

This paper shows experimental results on learning based randomized bin-picking combined with iterative visual recognition. We use the random forest to predict whether or not a robo…

cs.RO20163 cited

Initial Experiments on Learning-Based Randomized Bin-Picking Allowing Finger Contact with Neighboring Objects

Kensuke Harada, Weiwei Wan, Tokuo Tsuji +3

This paper proposes a novel method for randomized bin-picking based on learning. When a two-fingered gripper tries to pick an object from the pile, a finger often contacts a neighb…