Synchronous dual-arm manipulation by adult-sized humanoid robot

Hanjaya Mandala, Saeed Saeedvand, Jacky Baltes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper introduces a synchronous dual-arm manipulation with obstacle avoidance trajectory planning by an adult-size humanoid robot. In this regard, we propose a high precision 3D object coordinate tracking using LiDAR point cloud data and adopting Gaussian distribution into robot manipulation trajectory planning. We derived our 3D object detection into three methods included auto K-means clustering, deep learning object classification, and convex hull localization. Therefore, a lightweight 3D object classification based on a convolutional neural network (CNN) has been proposed that reached 91% accuracy with 0.34ms inference time on CPU. In empirical experiments, the Gaussian manipulation trajectory planning is applied adult-sized dual-arm robot, which shows efficient object placement with obstacle avoidance.

Original languageEnglish
Title of host publication2020 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728198231
DOIs
Publication statusPublished - 2020 Aug
Event2020 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2020 - Taipei, Taiwan
Duration: 2020 Aug 192020 Aug 21

Publication series

NameInternational Conference on Advanced Robotics and Intelligent Systems, ARIS
Volume2020-August
ISSN (Print)2374-3255
ISSN (Electronic)2572-6919

Conference

Conference2020 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2020
Country/TerritoryTaiwan
CityTaipei
Period2020/08/192020/08/21

Keywords

  • 3D perception
  • deep learning
  • humanoid robot
  • manipulation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence

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