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Tsukasa Ogasawara

7 accepted papers

2022

Soft-Jig: A Flexible Sensing Jig for Simultaneously Fixing and Estimating Orientation of Assembly Parts

ICRA 2022poster

For assembly tasks, it is essential to fix target parts firmly and accurately estimate their poses. Several rigid jigs for individual parts are frequently used in assembly factories to achieve a precise and time-efficient product assembly. However, providing customized jigs is time-consuming. In thi…

Cited by 5SourceScholar
2021

Assembly Sequences Based on Multiple Criteria Against Products with Deformable Parts

ICRA 2021poster

To generate assembly sequences that robots can easily handle, this study tackled assembly sequence generation (ASG) by considering two tradeoff objectives: (1) insertion conditions and (2) degrees of the constraints affecting the assembled parts. We propose a multi-objective genetic algorithm to bal…

Cited by 9SourceScholar
2019

A Parallel Gripper with a Universal Fingertip Device Using Optical Sensing and Jamming Transition for Maintaining Stable Grasps

IROS 2019poster

For a robotic gripper to perform as well as the human hand, the performance of the tactile sensing and grasping of the gripper must be improved. In this study, a parallel gripper with a universal fingertip device that combines both object holding using jamming transition and optical sensing is propo…

Cited by 10SourceScholar
2019

Adaptive Bingham Distribution Based Filter for SE (3) Estimation

ICRA 2019poster

Filter-based methods are a suitable option to deal with the burdensome 3D pose estimation problems for their incremental properties. The classical approaches use the Gaussian distribution to model the uncertainty of the pose parameters and recent work has begun to take advantage of the Bingham distr…

Cited by 0SourceScholar
2019

Fully Automated Annotation With Noise-Masked Visual Markers for Deep-Learning-Based Object Detection

RA-L 2019

Automated factories use deep-learning-based vision systems to accurately detect various products. However, training such vision systems requires manual annotation of a significant amount of data to optimize the large number of parameters of the deep convolutional neural networks. Such manual annotat

Cited by 29SourceScholar
2018

A Universal Gripper Using Optical Sensing to Acquire Tactile Information and Membrane Deformation

IROS 2018poster

The universal gripper has attracted attention due to its simple structure and advanced grasping ability for irregularly shaped objects. In this research, we propose a novel design for a granular-jamming-based gripper which uses a transparent filling and a semi-transparent membrane to allow optical s…

Cited by 39SourceScholar