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Li Q, Xu Y. Minimum‐time row transition control of a vision‐guided agricultural robot. J FIELD ROBOT 2021. [DOI: 10.1002/rob.22053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Qiang Li
- Department of Mechanical and Aerospace Engineering University of Central Florida Orlando Florida USA
| | - Yunjun Xu
- Department of Mechanical and Aerospace Engineering University of Central Florida Orlando Florida USA
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Georgiou C, Anderson S, Dodd T. Constructing informative Bayesian map priors: A multi-objective optimisation approach applied to indoor occupancy grid mapping. Int J Rob Res 2017. [DOI: 10.1177/0278364916687027] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The problem of simultaneous localisation and mapping (SLAM) has been addressed in numerous ways with different approaches aiming to produce faster, more robust solutions that yield consistent maps. This focus, however, has resulted in a number of solutions that perform poorly in challenging real life scenarios. In order to achieve improved performance and map quality this article proposes a novel method to construct informative Bayesian mapping priors through a multi-objective optimisation of prior map design variables defined using a source of prior information. This concept is explored for 2D occupancy grid SLAM, constructing such priors by extracting structural information from architectural drawings and identifying optimised prior values to assign to detected walls and empty space. Using the proposed method a contextual optimised prior can be constructed. This prior is found to yield better quantitative and qualitative performance than the commonly used non-informative prior, yielding an increase of over 20% in the [Formula: see text] metric. This is achieved without adding to the computational complexity of the SLAM algorithm, making it a good fit for time critical real life applications such as search and rescue missions.
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Affiliation(s)
- Christina Georgiou
- Department of Automatic Control and Systems Engineering, The University of Sheffield, UK
- PA Consulting Group, Cambridge Technology Centre, UK
| | - Sean Anderson
- Department of Automatic Control and Systems Engineering, The University of Sheffield, UK
| | - Tony Dodd
- Department of Automatic Control and Systems Engineering, The University of Sheffield, UK
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Lee K, Ryu SH, Yeon S, Cho H, Jun C, Kang J, Choi H, Hyeon J, Baek I, Jung W, Kim H, Doh NL. Accurate Continuous Sweeping Framework in Indoor Spaces With Backpack Sensor System for Applications to 3-D Mapping. IEEE Robot Autom Lett 2016. [DOI: 10.1109/lra.2016.2516585] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Abdul Hafez AH, Arora M, Krishna KM, Jawahar CV. Learning multiple experiences useful visual features for active maps localization in crowded environments. Adv Robot 2015. [DOI: 10.1080/01691864.2015.1090336] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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