Full metadata
Title
User Intent Detection and Control of a Soft Poly-Limb
Description
This work presents the integration of user intent detection and control in the development of the fluid-driven, wearable, and continuum, Soft Poly-Limb (SPL). The SPL utilizes the numerous traits of soft robotics to enable a novel approach to provide safe and compliant mobile manipulation assistance to healthy and impaired users. This wearable system equips the user with an additional limb made of soft materials that can be controlled to produce complex three-dimensional motion in space, like its biological counterparts with hydrostatic muscles. Similar to the elephant trunk, the SPL is able to manipulate objects using various end effectors, such as suction adhesion or a soft grasper, and can also wrap its entire length around objects for manipulation. User control of the limb is demonstrated using multiple user intent detection modalities. Further, the performance of the SPL studied by testing its capability to interact safely and closely around a user through a spatial mobility test. Finally, the limb’s ability to assist the user is explored through multitasking scenarios and pick and place tests with varying mounting locations of the arm around the user’s body. The results of these assessments demonstrate the SPL’s ability to safely interact with the user while exhibiting promising performance in assisting the user with a wide variety of tasks, in both work and general living scenarios.
Date Created
2018
Contributors
- Vale, Nicholas Marshall (Author)
- Polygerinos, Panagiotis (Thesis advisor)
- Zhang, Wenlong (Committee member)
- Artemiadis, Panagiotis (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
95 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.49247
Level of coding
minimal
Note
Masters Thesis Biomedical Engineering 2018
System Created
- 2018-06-01 08:05:37
System Modified
- 2021-08-26 09:47:01
- 3 years 2 months ago
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