Physical Human-Robot Interaction with Real Active Surfaces using Haptic Rendering on Point Clouds
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Date
2020
Publication Type
Conference Paper
ETH Bibliography
yes
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Abstract
During robot-assisted therapy of hemiplegic patients, interaction with the patient must be intrinsically safe. Straight-forward collision avoidance solutions can provide this safety requirement with conservative margins. These margins heavily reduce the robot’s workspace and make interaction with the patient’s unguided body parts impossible. However, interaction with the own body is highly beneficial from a therapeutic point of view. We tackle this problem by combining haptic rendering techniques with classical computer vision methods. Our proposed solution consists of a pipeline that
builds collision objects from point clouds in real-time and a controller that renders haptic interaction. The raw sensor data is processed to overcome noise and occlusion problems. Our proposed approach is validated on the 6 DoF exoskeleton ANYexo for direct impacts, sliding scenarios, and dynamic collision surfaces. The results show that this method has the potential to successfully prevent collisions and allow haptic interaction for highly dynamic environments. We believe that this work significantly adds to the usability of current exoskeletons by enabling virtual haptic interaction with the patient’s body parts in human-robot therapy.
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Publication status
published
Editor
Book title
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Journal / series
Volume
Pages / Article No.
9767 - 9773
Publisher
IEEE
Event
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020) (virtual)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Human Robot Interaction; Haptic rendering; Point cloud; Dynamic constraints; Haptic interaction
Organisational unit
09570 - Hutter, Marco / Hutter, Marco
03654 - Riener, Robert / Riener, Robert
Notes
Conference lecture held on October 28, 2020. Due to the Coronavirus (COVID-19) the conference was conducted virtually
Funding
Related publications and datasets
Is cited by: https://doi.org/10.3929/ethz-b-000575312
Is cited by: https://doi.org/10.3929/ethz-b-000702604