Abstract
This paper presents the control methodology and experimental results for the bilateral haptic teleoperation of a pneumatic actuated crawling robot. The two front legs of a robot are teleoperated via a pair of PHANToM haptic interfaces. The system gives the human operator the impression that he/she is physically moving and positioning the robot legs. As the legs hit the ground, the operator would also feel the reaction force via the haptic feedback provided by the PHANToMs. To reduce the physical effort by the operator, kinematic and power scaling factors are applied. For stable tele-operation, the closed loop system is controlled to behave like a common energetically passive mechanical tool interacting with the human operator (on the PHANToM's end) and the physical environment (on the Crawler's end). The control design strategy treats the pneumatic actuators as a two-port nonlinear spring. While the mechanical port of the actuator acts on the mechanical structure of the crawler's leg, the fluid port of the actuator is controlled to mimic the interaction between the pneumatic spring and the PHANToM, and to achieve co-ordination. The control methodology has been tested experimentally. While performing crawling motion, the RMS error of the robot foot placement error was 7mm, well within the crawler's foot diameter of 25.4mm.
Original language | English (US) |
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Title of host publication | ASME/BATH 2019 Symposium on Fluid Power and Motion Control, FPMC 2019 |
Publisher | American Society of Mechanical Engineers (ASME) |
ISBN (Electronic) | 9780791859339 |
DOIs | |
State | Published - 2020 |
Event | ASME/BATH 2019 Symposium on Fluid Power and Motion Control, FPMC 2019 - Longboat Key, United States Duration: Oct 7 2019 → Oct 9 2019 |
Publication series
Name | ASME/BATH 2019 Symposium on Fluid Power and Motion Control, FPMC 2019 |
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Conference
Conference | ASME/BATH 2019 Symposium on Fluid Power and Motion Control, FPMC 2019 |
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Country/Territory | United States |
City | Longboat Key |
Period | 10/7/19 → 10/9/19 |
Bibliographical note
Funding Information:This work is supported by the Center for Compact and Efficient Fluid Power funded by the NSF under grant: EEC-05080834. The authors also thank Dr. Wayne Book and members of Intelligent Machine Dynamics Laboratory at Georgia Tech. for their help while conducting experiments on the crawler robot.