Full metadata
Title
Mediating Human-Robot Collaboration through Mixed Reality Cues
Description
This work presents a communication paradigm, using a context-aware mixed reality approach, for instructing human workers when collaborating with robots. The main objective of this approach is to utilize the physical work environment as a canvas to communicate task-related instructions and robot intentions in the form of visual cues. A vision-based object tracking algorithm is used to precisely determine the pose and state of physical objects in and around the workspace. A projection mapping technique is used to overlay visual cues on tracked objects and the workspace. Simultaneous tracking and projection onto objects enables the system to provide just-in-time instructions for carrying out a procedural task. Additionally, the system can also inform and warn humans about the intentions of the robot and safety of the workspace. It was hypothesized that using this system for executing a human-robot collaborative task will improve the overall performance of the team and provide a positive experience to the human partner. To test this hypothesis, an experiment involving human subjects was conducted and the performance (both objective and subjective) of the presented system was compared with a conventional method based on printed instructions. It was found that projecting visual cues enabled human subjects to collaborate more effectively with the robot and resulted in higher efficiency in completing the task.
Date Created
2017
Contributors
- Kalpagam Ganesan, Ramsundar (Author)
- Ben Amor, Hani (Thesis advisor)
- Yang, Yezhou (Committee member)
- Zhang, Yu (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
56 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.44055
Level of coding
minimal
Note
Masters Thesis Electrical Engineering 2017
System Created
- 2017-06-01 01:32:18
System Modified
- 2021-08-26 09:47:01
- 3 years 2 months ago
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