TY - GEN
T1 - Motion-Based Control Interface for Intuitive and Efficient Teleoperation of Construction Robots
AU - Rasheed, Usman
AU - Liang, Xiaoyun
AU - Cai, Jiannan
AU - Li, Shuai
AU - Hu, Yuqing
N1 - Publisher Copyright:
© International Conference on Computing in Civil Engineering 2023.All rights reserved.
PY - 2024
Y1 - 2024
N2 - Robotic teleoperation is regarded as a promising method of assisting workers in performing construction activities while avoiding potentially dangerous conditions. However, the control interface of conventional teleoperation systems relies on physical devices, such as a keyboard and joystick, to input control commands, which cannot be intuitively mapped to robot movement, and thus affecting the teleoperation performance of non-expert users. In this research, we present a novel human-robot interface to map human arm movement to robotic arm motion for intuitive teleoperation. Firstly, the human arm is tracked in real-Time through a motion capturing system, that is, OptiTrack. The 3D location data is then streamed to robot operating system (ROS) and is used for motion planning of the robotic arm in MoveIt. Finally, the interface is demonstrated in a teleoperated pick-And-place task through robotic simulation, and the usability of the developed framework is compared to that of a joystick-based teleoperation system.
AB - Robotic teleoperation is regarded as a promising method of assisting workers in performing construction activities while avoiding potentially dangerous conditions. However, the control interface of conventional teleoperation systems relies on physical devices, such as a keyboard and joystick, to input control commands, which cannot be intuitively mapped to robot movement, and thus affecting the teleoperation performance of non-expert users. In this research, we present a novel human-robot interface to map human arm movement to robotic arm motion for intuitive teleoperation. Firstly, the human arm is tracked in real-Time through a motion capturing system, that is, OptiTrack. The 3D location data is then streamed to robot operating system (ROS) and is used for motion planning of the robotic arm in MoveIt. Finally, the interface is demonstrated in a teleoperated pick-And-place task through robotic simulation, and the usability of the developed framework is compared to that of a joystick-based teleoperation system.
UR - http://www.scopus.com/inward/record.url?scp=85184280179&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85184280179&partnerID=8YFLogxK
U2 - 10.1061/9780784485224.057
DO - 10.1061/9780784485224.057
M3 - Conference contribution
AN - SCOPUS:85184280179
T3 - Computing in Civil Engineering 2023: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023
SP - 470
EP - 478
BT - Computing in Civil Engineering 2023
A2 - Turkan, Yelda
A2 - Louis, Joseph
A2 - Leite, Fernanda
A2 - Ergan, Semiha
PB - American Society of Civil Engineers (ASCE)
T2 - ASCE International Conference on Computing in Civil Engineering 2023: Data, Sensing, and Analytics, i3CE 2023
Y2 - 25 June 2023 through 28 June 2023
ER -