An Indoor Navigation System Based on Stereo Camera and Inertial Sensors with Points and Lines

Yang, Bo; Xu, Xiaosu; Zhang, Tao; Yao, Li; Tong, Jinwu

doi:10.1155/2018/4801584

Cited by 3 publications

(1 citation statement)

References 42 publications

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“…Zhou et al [20] proposed a combined method based on images from a smartphone camera capturing the surrounding scene and pedestrian dead reckoning (PDR) to determine the pedestrian’s trajectory with an accuracy of about 0.56 m. Using embedded inertial sensors [21] and PDR [22] by updating the current position through measuring the length and title of each step, enabled reaching an error of 1.96 m. A similar multisensory approach improved this up to 1.46 m [23]. A combination with stereo cameras has improved the accuracy up to 0.677 m [24]. A combination with Bluetooth beacons can provide an average error rate around 2.53% [25].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings

Almadani

Orujov

Maskeliūnas

et al. 2019

Sensors

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The ability to precisely locate and navigate a partially impaired or a blind person within a building is increasingly important for a wide variety of public safety and localization services. In this paper, we explore indoor localization algorithms using Bluetooth Low Energy (BLE) beacons. We propose using the BLE beacon’s received signal strength indication (RSSI) and the geometric distance from the current beacon to the fingerprint point in the framework of fuzzy logic for calculating the Euclidean distance for the subsequent determination of location. According to our results, the fingerprinting algorithm with fuzzy logic type-2 (hesitant fuzzy sets) is fit for use as an indoor localization method with BLE beacons. The average error of localization is only 0.43 m, and the algorithm obtains a navigation precision of 98.2 ± 1%. This precision confirms that the algorithms provide great aid to a visually impaired person in unknown spaces, especially those designed without physical tactile guides, as confirmed by low Fréchet and Hausdorff distance values and high navigation efficiency index (NEI) scores.

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Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings

Almadani

Orujov

Maskeliūnas

et al. 2019

Sensors

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A Fire Reconnaissance Robot Based on SLAM Position, Thermal Imaging Technologies, and AR Display

Feng

Niu

et al. 2019

Sensors

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Due to hot toxic smoke and unknown risks under fire conditions, detection and relevant reconnaissance are significant in avoiding casualties. A fire reconnaissance robot was therefore developed to assist in the problem by offering important fire information to fire fighters. The robot consists of three main systems, a display operating system, video surveillance, and mapping and positioning navigation. Augmented reality (AR) goggle technology with a display operating system was also developed to free fire fighters’ hands, which enables them to focus on rescuing processes and not system operation. Considering smoke disturbance, a thermal imaging video surveillance system was included to extract information from the complicated fire conditions. Meanwhile, a simultaneous localization and mapping (SLAM) technology was adopted to build the map, together with the help of a mapping and positioning navigation system. This can provide a real-time map under the rapidly changing fire conditions to guide the fire fighters to the fire sources or the trapped occupants. Based on our experiments, it was found that all the tested system components work quite well under the fire conditions, while the video surveillance system produces clear images under dense smoke and a high-temperature environment; SLAM shows a high accuracy with an average error of less than 3.43%; the positioning accuracy error is 0.31 m; and the maximum error for the navigation system is 3.48%. The developed fire reconnaissance robot can provide a practically important platform to improve fire rescue efficiency to reduce the fire casualties of fire fighters.

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Harris hawks optimization algorithm and BP neural network for ultra-wideband indoor positioning

Chen

Liu

et al. 2022

MBE

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<abstract> <p>Traditional back propagation neural networks (BPNNs) for ultrawideband (UWB) indoor localization can effectively improve localization accuracy, although there is high likelihood of becoming trapped in nearby minima. To solve this problem, the random weights and thresholds of the BPNN are optimized using the Harris Hawks optimization algorithm (HHO) to obtain the optimal global solution to enhance the UWB indoor positioning accuracy and NLOS resistance. The results show that the predicted trajectory of the HHO and BPNN hybrid algorithm (HHO-BP) matches the actual position in the two-dimensional localization scenario with four base stations; the optimized average positioning error is effectively reduced in both indoor LOS and NLOS environments. In the LOS environment, the total mean error of the traditional BPNN algorithm is 6.52 cm, which is 26.99% better than the UWB measurement error; in the NLOS environment, the total mean error of the conventional BPNN is 14.82 cm, which is 50.08% better than the UWB measurement error. The HHO–BP algorithm is further optimized on this basis, and the total mean error in the LOS environment is 4.50 cm, which is 22.57% better than the conventional BPNN algorithm; in the NLOS environment, the total mean error is 9.56 cm, which is 17.54% better than the conventional BPNN algorithm. The experimental findings suggest that the approach has greater calibration accuracy and stability than BPNN, making it a viable choice for scenarios requiring high positional precision.</p> </abstract>

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An Indoor Navigation System Based on Stereo Camera and Inertial Sensors with Points and Lines

Cited by 3 publications

References 42 publications

Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings

Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings

A Fire Reconnaissance Robot Based on SLAM Position, Thermal Imaging Technologies, and AR Display

Harris hawks optimization algorithm and BP neural network for ultra-wideband indoor positioning

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