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Title: Design Interface Mapping for Efficient Free-form Tele-manipulation
Motion tracking interfaces are intuitive for free-form teleoperation tasks. However, efficient manipulation control can be difficult with such interfaces because of issues like the interference of unintended motions and the limited precision of human motion control. The limitation in control efficiency reduces the operator's performance and increases their workload and frustration during robot teleoperation. To improve the efficiency, we proposed separating controlled degrees of freedom (DoFs) and adjusting the motion scaling ratio of a motion tracking interface. The motion tracking of handheld controllers from a Virtual Reality system was used for the interface. We separated the translation and rotational control into: 1) two controllers held in the dominant and non-dominant hands and 2) hand pose tracking and trackpad inputs of a controller. We scaled the control mapping ratio based on 1) the environmental constraints and 2) the teleoperator's control speed. We further conducted a user study to investigate the effectiveness of the proposed methods in increasing efficiency. Our results show that the separation of position and orientation control into two controllers and the environment-based scaling methods perform better than their alternatives.  more » « less
Award ID(s):
2024802 1922761
NSF-PAR ID:
10448498
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Page Range / eLocation ID:
6221 to 6226
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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