Constructing informative Bayesian map priors: A multi-objective optimisation approach applied to indoor occupancy grid mapping
- Submitting institution
-
Staffordshire University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 6796
- Type
- D - Journal article
- DOI
-
10.1177/0278364916687027
- Title of journal
- The International Journal of Robotics Research
- Article number
- -
- First page
- 274-291
- Volume
- 36
- Issue
- 3
- ISSN
- 0278-3649
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2017
- URL
-
https://journals.sagepub.com/doi/10.1177/0278364916687027
- 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
-
2
- Research group(s)
-
B - Centre for Smart Systems, AI and Cybersecurity (CSSAIC)
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Simultaneous localisation and mapping (SLAM) is critical to achieving autonomy for mobile robots and autonomous vehicles. However, SLAM is challenging in real world scenarios and typically does not take account of prior knowledge about the environment. This paper demonstrates, for the first time, that using prior information in indoor settings significantly improves performance. The results of this work strongly influenced the development of a work package in the EPSRC Programme Grant, Pervasive Sensing for Buried Pipes (EP/S016813/1).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -