TY - GEN
T1 - Object recognition and user interface design for vision-based autonomous robotic grasping point determination
AU - Cheng, Fang Che
AU - Yen, Chia Ching
AU - Jeng, Tay Sheng
N1 - Funding Information:
This research is developed by Robot Aided Creation and Construction (RAC-Coon) of National Cheng Kung University and the Department of Architecture. We would like to thank Dr.Yi-Hsuan Tu provides the resource of computer vision and support, Dr. Yang-Ting Shen for advice on the human-computer collaboration, Dr. Sheng-Fen Chien for advice on the pose estimation, Ying-Syu Huang for providing the robotic coding, and Yu-Xun Chen for providing the method of calibration and coding.
Publisher Copyright:
© 2021 and published by the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong.
PY - 2021
Y1 - 2021
N2 - The integration of Robot Operating System (ROS) with Human-Machine Collaboration (HMC) currently represents the future tendency toward Autonomous Robotic In-Situ Assembly on Construction Sites. In comparison with the industrial environment, construction sites nowadays are extremely complex and unpredictable, due to the different building components and customized design.This paper presents a visual-based object recognition method and user interface enabling on-site robot arms to autonomously handle building components, to build specific designs without the influence of material, shape, and environment. The implementation is an object recognition approach that serves with KUKA industrial robotic manipulator along with an RGB-depth stereo camera in an eye-in-hand configuration to grasp and manipulate found elements to build the desired structure. Opportunities for using vision-based autonomous robotic in-situ assembly on construction sites are reviewed.
AB - The integration of Robot Operating System (ROS) with Human-Machine Collaboration (HMC) currently represents the future tendency toward Autonomous Robotic In-Situ Assembly on Construction Sites. In comparison with the industrial environment, construction sites nowadays are extremely complex and unpredictable, due to the different building components and customized design.This paper presents a visual-based object recognition method and user interface enabling on-site robot arms to autonomously handle building components, to build specific designs without the influence of material, shape, and environment. The implementation is an object recognition approach that serves with KUKA industrial robotic manipulator along with an RGB-depth stereo camera in an eye-in-hand configuration to grasp and manipulate found elements to build the desired structure. Opportunities for using vision-based autonomous robotic in-situ assembly on construction sites are reviewed.
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M3 - Conference contribution
AN - SCOPUS:85104601193
T3 - Projections - Proceedings of the 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia, CAADRIA 2021
SP - 633
EP - 642
BT - Projections - Proceedings of the 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia, CAADRIA 2021
A2 - Globa, Anastasia
A2 - van Ameijde, Jeroen
A2 - Fingrut, Adam
A2 - Kim, Nayeon
A2 - Lo, Tian Tian Sky
PB - The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA)
T2 - 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia: Projections, CAADRIA 2021
Y2 - 29 March 2021 through 1 April 2021
ER -