2018
DOI: 10.1016/j.robot.2017.10.019
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Embedding SLAM algorithms: Has it come of age?

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Cited by 52 publications
(30 citation statements)
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“…In previous sections, we described some of the challenges in designing and implementing an UAV for interior WTB inspection. Among other issues, autonomous interior UAVs have been limited by the computing power in the embedded computers [118]. To partially alleviate this problem, cameras such as Intel Realsense [156] or OpenMV [157] could be used.…”
Section: Discussion and Future Of Interior Wtb Inspectionsmentioning
confidence: 99%
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“…In previous sections, we described some of the challenges in designing and implementing an UAV for interior WTB inspection. Among other issues, autonomous interior UAVs have been limited by the computing power in the embedded computers [118]. To partially alleviate this problem, cameras such as Intel Realsense [156] or OpenMV [157] could be used.…”
Section: Discussion and Future Of Interior Wtb Inspectionsmentioning
confidence: 99%
“…However, there is a large amount of data from the surrounding environment that needs to be updated constantly, connecting each data point perceived by the sensors together to form a map. As a real-time solution, SLAM requires high amount of computing power to estimate the distances between objects several times every second [118] in order for the UAV to constantly avoid collision. Moreover, LiDARs and other ToF sensors are subject to scattering or multipath interference [119].…”
Section: Obstacle Avoidance and Localizationmentioning
confidence: 99%
“…In SLAMBench2.0 [3] and SLAMBench3.0 [4], more SLAM algorithms are supported by a SLAM API and an I/O system. Similar benchmarking works have been performed in [5] and [6]. As the application of SLAM algorithms in robotics and computer vision is growing, it is becoming apparent that a more sophisticated approach to benchmarking is needed [7].…”
Section: Introductionmentioning
confidence: 94%
“…Customized hardware for the VI-SLAM can realize the function of robots, and AR/VR devices are applied to sports, navigation, teaching, and entertainment. Therefore, a strong demand exists for SLAM miniaturization and weight reduction, prefacing the future of embedded SLAM [122].…”
Section: Hardware Integration and Multi-sensor Fusionmentioning
confidence: 99%