Sensor Technologies and Simultaneous Localization and Mapping (SLAM)

Chong, Teak-Wei; Tang, Xinyue; Leng, Chuntao; Yogeswaran, M.; Ng, Oon-Ee; Chong, Yu Zheng

doi:10.1016/j.procs.2015.12.336

Cited by 69 publications

(39 citation statements)

References 24 publications

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“…They locate objects from the echo of a signal that is bounced off the object. Ultrasonic sensor, which is a sub-category of SONARs, is widely utilised for robots [16]. They use sound waves in the ultrasonic range (above 20kHz) which are not audible for human beings.…”

Section: A Acoustic Sensorsmentioning

confidence: 99%

Sensors, SLAM and Long-term Autonomy: A Review

Zaffar

Ehsan

McDonald-Maier

2018

2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

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Simultaneous Localization and Mapping, commonly known as SLAM, has been an active research area in the field of Robotics over the past three decades. For solving the SLAM problem, every robot is equipped with either a single sensor or a combination of similar/different sensors. This paper attempts to review, discuss, evaluate and compare these sensors. Keeping an eye on future, this paper also assesses the characteristics of these sensors against factors critical to the long-term autonomy challenge.

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Section: A Acoustic Sensorsmentioning

confidence: 99%

Sensors, SLAM and Long-term Autonomy: A Review

Zaffar

Ehsan

McDonald-Maier

2018

2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

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“…Mapping the spatial information of an environment requires spatial sensors to which SLAM algorithms can be applied. The two most popular sensor modalities used in SLAM are raw range scan sensors and feature (landmark) based sensors (whether extracted from scans or images) [11,12].…”

Section: So What Are the Benefits Of Geospatial Slam?mentioning

confidence: 99%

Situations in Construction of 3D Mapping for Slam

Thuy

Shydlouski

2018

MATEC Web Conf.

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Nowadays, the simultaneous localization and mapping (SLAM) approach has become one of the most advanced engineering methods used for mobile robots to build maps in unknown or inaccessible spaces. Update maps before a certain area while tracking current location and distance. The motivation behind writing this paper is mainly to help us better understand about SLAM and the study situation of SLAM in the world today. Through this, we find the optimal algorithm for moving robots in three dimensions.

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“…For example, it takes at least 6 s for Tritech MiniKing imaging sonar to complete a scan because of its mechanical limits, and this time can increase dramatically depending on the range setting; at a 50 m range setting, a complete scan takes about 15 s [14]. Despite these challenges, sonar sensors are popular in mobile robot applications because of their low cost [15]. Sonar sensors are mostly used in underwater applications because sound can travel farther underwater than radio waves and light [16].…”

Section: Introductionmentioning

confidence: 99%

Eavesdropping like a bat: Towards fusing active and passive sonar for a case study in simultaneous localization and mapping

Shirazi

Abaid

2021

IET Radar Sonar & Navi

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Among so-called active sensors that use self-generated signals, sonar sensors are more challenging to implement than lidar and radar due in part to their limited angular field of sensing. A common solution to this challenge is scanning sensors that sweep an angular range with successive measurements. However, scanning sensors are particularly problematic for sonar because of the relatively slow sound speed and the inertia of the sonar head. Studies of bat behaviour suggest that bats may eavesdrop on their conspecifics during group flight. In other words, they fuse information gathered by their own active sonar with information they receive by passively listening to peers. Because bats are extremely skilled in using sonar, this behaviour inspired an investigation into whether fusing active and passive sonar can be a solution to the challenges of implementing sonar sensors. A model of fused sensing is defined, and a numerical simulation is used to answer this question on the test bed problem of simultaneous localization and mapping (SLAM). The simulation results show that when the angular range of active sonar and associated noise is relatively small, the robot's performance in solving SLAM is improved.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Sensor Technologies and Simultaneous Localization and Mapping (SLAM)

Cited by 69 publications

References 24 publications

Sensors, SLAM and Long-term Autonomy: A Review

Sensors, SLAM and Long-term Autonomy: A Review

Situations in Construction of 3D Mapping for Slam

Eavesdropping like a bat: Towards fusing active and passive sonar for a case study in simultaneous localization and mapping

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