Potentially guided bidirectionalized RRT* for fast optimal path planning in cluttered environments
- Submitting institution
-
Manchester Metropolitan University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2351
- Type
- D - Journal article
- DOI
-
10.1016/j.robot.2018.06.013
- Title of journal
- Robotics and Autonomous Systems
- Article number
- -
- First page
- 13
- Volume
- 108
- Issue
- -
- ISSN
- 0921-8890
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2018
- URL
-
https://e-space.mmu.ac.uk/620995/
- 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
-
3
- Research group(s)
-
A - Data Science
- Citation count
- 26
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents an innovative solution targeting motion planning for robots in highly cluttered environments. Extensions and applications have included drones (Lin et al., 2019; Wu et al. 2020), mobile manipulators (Thakar et al., 2020), underwater systems (Fu et al. 2020), and motion tracking (Zhong et al., 2020; Shi et al., 2020). The National Centre for Robotics and Automation (NCRA) in Pakistan is extending this work by building low-cost robots for disaster recovery (Umar Shahbaz, Chair NCRA, UmarShahbaz@ncra.org.pk). An NCAI sponsored PhD studentship has been competitively awarded to extend the research into overbuilt honeycomb environments (Yasar Ayaz, Chair NCAI, yasar@smme.nust.edu.pk).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -