Comparison of Various SLAM Systems for Mobile Robot in an Indoor Environment

Филипенко, М. Л.; Afanasyev, Ilya

doi:10.1109/is.2018.8710464

Cited by 137 publications

(63 citation statements)

References 48 publications

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“…This is commonly known as Simultaneous Localization and Mapping (SLAM). The quality (accuracy of the trajectory followed) of the SLAM depends strongly on the hardware used [29]. Depth estimation (such as enbaled by, e.g., LIDAR) can significantly improve the quality of the SLAM [70], this, however, also comes with an increased computational complexity.…”

Section: Base Sensorsmentioning

confidence: 99%

A review of the challenges in mobile manipulation: systems design and RoboCup challenges

Sereinig

Werth

Faller

2020

Elektrotech. Inftech.

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Mobile robotics is already well established in today’s production lines. Navigation, control and perception for mobile robots are vivid fields of research fostering advances in Industry 4.0. In order to increase the flexibility of such mobile platforms, it is also common practice to add serial manipulator arms to their yielding systems with nine degrees of freedom and more. These platforms are not limited to industry but are supportive in various field such as service, assistance, teleoperation and also rehabilitation. Due to the operation of such increasingly complex systems in less structured and dynamic environments - often in close contact with humans - more demanding challenges evolve in terms of systems design, control and sensors. These challenges are also reflected in the various RoboCup leagues. In this paper, we discuss state-of-the-art developments in mobile manipulation using developments and work done in the context of the RoboCup competition as design examples. Additionally, we elaborate on the recent challenges of the RoboCup Rescue League as well as on the RoboCup@Work League.

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Section: Base Sensorsmentioning

confidence: 99%

A review of the challenges in mobile manipulation: systems design and RoboCup challenges

Sereinig

Werth

Faller

2020

Elektrotech. Inftech.

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“…Over the years, the researches of performance comparison of methods that have emerged before significantly increased as well [32]. Sualeh et al [33] recently have projected into future potential SLAM studies as well as scanning past studies [34].…”

Section: Literature Reviewmentioning

confidence: 99%

Exact flow of particles using for state estimations in unmanned aerial systems` navigation

2020

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The navigation is a substantial issue in the field of robotics. Simultaneous Localization and Mapping (SLAM) is a principle for many autonomous navigation applications, particularly in the Global Navigation Satellite System (GNSS) denied environments. Many SLAM methods made substantial contributions to improve its accuracy, cost, and efficiency. Still, it is a considerable challenge to manage robust SLAM, and there exist several attempts to find better estimation algorithms for it. In this research, we proposed a novel Bayesian filtering based Airborne SLAM structure for the first time in the literature. We also presented the mathematical background of the algorithm, and the SLAM model of an autonomous aerial vehicle. Simulation results emphasize that the new Airborne SLAM performance with the exact flow of particles using for recursive state estimations superior to other approaches emerged before, in terms of accuracy and speed of convergence. Nevertheless, its computational complexity may cause real-time application concerns, particularly in high-dimensional state spaces. However, in Airborne SLAM, it can be preferred in the measurement environments that use low uncertainty sensors because it gives more successful results by eliminating the problem of degeneration seen in the particle filter structure.

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“…Before defining which sensor and algorithm will be used, it is important to understand the advantages and disadvantages of each solution with comparisons, as in [4]. Their data was collected from a moving robot in a closed environment, using three different sensors: 2D LiDAR, monocular and ZED stereo cameras.…”

Section: Related Workmentioning

confidence: 99%

Development of Embedded Algorithm for Visual Simultaneous Localization and Mapping

Rosa

Silveira

Mélo

et al. 2019

Anais Estendidos Do XXXII Conference on Graphics, Patterns and Images (SIBRAPI Estendido 2019)

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The Simultaneous Localization and Mapping (SLAM) problem is recurrent in today's robotics. One challenge of it is the extensive computational cost to create complex maps in real-time. Various applications, mainly search and rescue operate in GPS denied scenarios, with possible difficulty communicating with an external base. A portable SLAM system capable of being run in a microcomputer would greatly help such operations. This paper mentions the unfinished into this topic and discusses further steps that shall be taken in the upcoming months.

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Comparison of Various SLAM Systems for Mobile Robot in an Indoor Environment

Cited by 137 publications

References 48 publications

A review of the challenges in mobile manipulation: systems design and RoboCup challenges

A review of the challenges in mobile manipulation: systems design and RoboCup challenges

Exact flow of particles using for state estimations in unmanned aerial systems` navigation

Development of Embedded Algorithm for Visual Simultaneous Localization and Mapping

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