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Corrective Shared Autonomy for Addressing Task Variability
- Source :
- IEEE Robot Autom Lett
- Publication Year :
- 2021
-
Abstract
- Many tasks, particularly those involving interaction with the environment, are characterized by high variability, making robotic autonomy difficult. One flexible solution is to introduce the input of a human with superior experience and cognitive abilities as part of a shared autonomy policy. However, current methods for shared autonomy are not designed to address the wide range of necessary corrections (e.g., positions, forces, execution rate, etc.) that the user may need to provide to address task variability. In this paper, we present corrective shared autonomy, where users provide corrections to key robot state variables on top of an otherwise autonomous task model. We provide an instantiation of this shared autonomy paradigm and demonstrate its viability and benefits such as low user effort and physical demand via a system-level user study on three tasks involving variability situated in aircraft manufacturing.<br />Comment: IEEE Robotics and Automation Letters (RA-L)
- Subjects :
- FOS: Computer and information sciences
0209 industrial biotechnology
Control and Optimization
Computer science
media_common.quotation_subject
Biomedical Engineering
02 engineering and technology
Article
Task (project management)
Computer Science - Robotics
020901 industrial engineering & automation
0203 mechanical engineering
Artificial Intelligence
Human–computer interaction
Situated
media_common
Robot kinematics
Mechanical Engineering
Cognition
Computer Science Applications
Human-Computer Interaction
020303 mechanical engineering & transports
Control and Systems Engineering
Task analysis
Key (cryptography)
Robot
Computer Vision and Pattern Recognition
Robotics (cs.RO)
Autonomy
Subjects
Details
- ISSN :
- 23773766
- Volume :
- 6
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- IEEE robotics and automation letters
- Accession number :
- edsair.doi.dedup.....4bfa3b0d7c7a83c200470f71336aa627