A hierarchical system for a distributed representation of the peripersonal space of a humanoid robot
- Submitting institution
-
Middlesex University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1408
- Type
- D - Journal article
- DOI
-
10.1109/TAMD.2014.2332875
- Title of journal
- IEEE Transactions on Autonomous Mental Development
- Article number
- -
- First page
- 259
- Volume
- 6
- Issue
- 4
- ISSN
- 1943-0604
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2014
- URL
-
http://eprints.mdx.ac.uk/19782/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
10
- Research group(s)
-
-
- Citation count
- 17
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Emulation of human arm reaching skills in robots is typically performed using a set of complex transformations requiring detailed knowledge of the environment and the robot kinematics. In this work, a robot learns its internal models and the external configuration of the environment by self-observation of its own interaction with surrounding objects. This paper is significant for the robotics community because of the practical skills the robot achieves through an integrated and autonomous learning process, and for the computational neuroscience community for how it demonstrates the capabilities of a simple but biologically plausible neural structure on learning practical sensorimotor tasks.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -