Mobile Robotics in a Random Finite Set Framework
This paper describes the Random Finite Set approach to Bayesian mobile robotics, which is based on a natural multi-object filtering framework, making it well suited to both single and swarm-based mobile robotic applications. By modeling the measurements and feature map as random finite sets (RFSs),...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Book Chapter |
| Published: |
Springer
2014
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/24990 |
| _version_ | 1848751581993893888 |
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| author | Mullane, J. Vo, Ba-Ngu Adams, M. Vo, Ba Tuong |
| author2 | Ying tan |
| author_facet | Ying tan Mullane, J. Vo, Ba-Ngu Adams, M. Vo, Ba Tuong |
| author_sort | Mullane, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper describes the Random Finite Set approach to Bayesian mobile robotics, which is based on a natural multi-object filtering framework, making it well suited to both single and swarm-based mobile robotic applications. By modeling the measurements and feature map as random finite sets (RFSs), joint estimates the number and location of the objects (features) in the map can be generated. In addition, it is shown how the path of each robot can be estimated if required. The framework differs dramatically from existing approaches since both data association and feature management routines are integrated into a single recursion. This makes the framework well suited to multi-robot scenarios due to the ease of fusing multiple map estimates from swarm members, as well as mapping robustness in the presence of other mobile robots which may induce false map measurements. An overview of developments thus far is presented, with implementations demonstrating the merits of the framework on simulated and experimental datasets. |
| first_indexed | 2025-11-14T07:55:01Z |
| format | Book Chapter |
| id | curtin-20.500.11937-24990 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:55:01Z |
| publishDate | 2014 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-249902023-02-27T07:34:30Z Mobile Robotics in a Random Finite Set Framework Mullane, J. Vo, Ba-Ngu Adams, M. Vo, Ba Tuong Ying tan Yuhui Shi Yi Chai Guoyin Wang mobile robotics Bayesian estimation Probability Hypothesis Density random finite sets This paper describes the Random Finite Set approach to Bayesian mobile robotics, which is based on a natural multi-object filtering framework, making it well suited to both single and swarm-based mobile robotic applications. By modeling the measurements and feature map as random finite sets (RFSs), joint estimates the number and location of the objects (features) in the map can be generated. In addition, it is shown how the path of each robot can be estimated if required. The framework differs dramatically from existing approaches since both data association and feature management routines are integrated into a single recursion. This makes the framework well suited to multi-robot scenarios due to the ease of fusing multiple map estimates from swarm members, as well as mapping robustness in the presence of other mobile robots which may induce false map measurements. An overview of developments thus far is presented, with implementations demonstrating the merits of the framework on simulated and experimental datasets. 2014 Book Chapter http://hdl.handle.net/20.500.11937/24990 10.1007/978-3-642-21524-7_64 Springer restricted |
| spellingShingle | mobile robotics Bayesian estimation Probability Hypothesis Density random finite sets Mullane, J. Vo, Ba-Ngu Adams, M. Vo, Ba Tuong Mobile Robotics in a Random Finite Set Framework |
| title | Mobile Robotics in a Random Finite Set Framework |
| title_full | Mobile Robotics in a Random Finite Set Framework |
| title_fullStr | Mobile Robotics in a Random Finite Set Framework |
| title_full_unstemmed | Mobile Robotics in a Random Finite Set Framework |
| title_short | Mobile Robotics in a Random Finite Set Framework |
| title_sort | mobile robotics in a random finite set framework |
| topic | mobile robotics Bayesian estimation Probability Hypothesis Density random finite sets |
| url | http://hdl.handle.net/20.500.11937/24990 |