Search Results for author: Weiwei Wan

Found 8 papers, 2 papers with code

In-Rack Test Tube Pose Estimation Using RGB-D Data

no code implementations21 Aug 2023 Hao Chen, Weiwei Wan, Masaki Matsushita, Takeyuki Kotaka, Kensuke Harada

Accurate robotic manipulation of test tubes in biology and medical industries is becoming increasingly important to address workforce shortages and improve worker safety.

Point Cloud Registration Pose Estimation

Online Initialization and Extrinsic Spatial-Temporal Calibration for Monocular Visual-Inertial Odometry

no code implementations12 Apr 2020 Weibo Huang, Hong Liu, Weiwei Wan

To compensate for the impact of time offset, our method includes two short-term motion interpolation algorithms for the camera and IMU pose estimation.

Motion Interpolation Pose Estimation

Functionally Divided Manipulation Synergy for Controlling Multi-fingered Hands

no code implementations26 Mar 2020 Kazuki Higashi, Keisuke Koyama, Ryuta Ozawa, Kazuyuki Nagata, Weiwei Wan, Kensuke Harada

Synergy supplies a practical approach for expressing various postures of a multi-fingered hand.

Robotics

Selecting and Designing Grippers for an Assembly Task in a Structured Approach

no code implementations9 Mar 2020 Jingren Xu, Keisuke Koyama, Weiwei Wan, Yukiyasu Domae, Kensuke Harada

In this paper, we present a structured approach of selecting and designing a set of grippers for an assembly task.

Robotics

Planning an Efficient and Robust Base Sequence for a Mobile Manipulator Performing Multiple Pick-and-place Tasks

no code implementations22 Jan 2020 Jingren Xu, Kensuke Harada, Weiwei Wan, Toshio Ueshiba, Yukiyasu Domae

In this paper, we address efficiently and robustly collecting objects stored in different trays using a mobile manipulator.

Robotics

Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process

no code implementations4 Oct 2019 Yan Wang, Kensuke Harada, Weiwei Wan

Complex and skillful motions in actual assembly process are challenging for the robot to generate with existing motion planning approaches, because some key poses during the human assembly can be too skillful for the robot to realize automatically.

Motion Planning

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