Accurate position tracking with a single UWB anchor

Cao, Yanjun; Yang, Changli; Li, Rui; Knoll, Alois; Beltrame, Giovanni

doi:10.1109/icra40945.2020.9197345

Cited by 56 publications

(34 citation statements)

References 22 publications

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“…On the other hand, UWB and vision systems have been combined to improve the estimation of the position in the workspace [ 23 ]. Other strategies bet on the fusion of UWB data with those coming from INS [ 24 ], and Optitrack [ 25 ]. Additionally, it has been tried to improve UWB systems’ results on a platform of mobile robots using Gaussian processes [ 26 ] and neural networks [ 27 ].…”

Section: Background and Related Workmentioning

confidence: 99%

Sensor Information Sharing Using a Producer-Consumer Algorithm on Small Vehicles

Vazquez-Lopez

Lozada

Sandoval-Gutierrez

et al. 2021

Sensors

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There are several tools, frameworks, and algorithms to solve information sharing from multiple tasks and robots. Some applications such as ROS, Kafka, and MAVLink cover most problems when using operating systems. However, they cannot be used for particular problems that demand optimization of resources. Therefore, the objective was to design a solution to fit the resources of small vehicles. The methodology consisted of defining the group of vehicles with low performance or are not compatible with high-level known applications; design a reduced, modular, and compatible architecture; design a producer-consumer algorithm that adjusts to the simultaneous localization and communication of multiple vehicles with UWB sensors; validate the operation with an interception task. The results showed the feasibility of performing architecture for embedded systems compatible with other applications managing information through the proposed algorithm allowed to complete the interception task between two vehicles. Another result was to determine the system’s efficiency by scaling the memory size and comparing its performance. The work’s contributions show the areas of opportunity to develop architectures focusing on the optimization of robot resources and complement existing ones.

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Section: Background and Related Workmentioning

confidence: 99%

Sensor Information Sharing Using a Producer-Consumer Algorithm on Small Vehicles

Vazquez-Lopez

Lozada

Sandoval-Gutierrez

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…UWB modules estimate the position of a UWB tag within the space spanned by three or more UWB beacons through triangulation. There have been robotics applications combining onboard UWB tag with inertial measurement units (IMU) or gyroscope sensors, to be localized in environments with pre-deployed UWB beacons ( Mueller et al, 2015 ; Mai et al, 2018 ; Cao et al, 2020 ). Nevertheless, to our knowledge the uses of UWB modules and DRL methods have not been reported in the literature for navigation aids to BVI users.…”

Section: Related Workmentioning

confidence: 99%

Assistive Navigation Using Deep Reinforcement Learning Guiding Robot With UWB/Voice Beacons and Semantic Feedbacks for Blind and Visually Impaired People

Liu

Huang

et al. 2021

Front. Robot. AI

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Facilitating navigation in pedestrian environments is critical for enabling people who are blind and visually impaired (BVI) to achieve independent mobility. A deep reinforcement learning (DRL)–based assistive guiding robot with ultrawide-bandwidth (UWB) beacons that can navigate through routes with designated waypoints was designed in this study. Typically, a simultaneous localization and mapping (SLAM) framework is used to estimate the robot pose and navigational goal; however, SLAM frameworks are vulnerable in certain dynamic environments. The proposed navigation method is a learning approach based on state-of-the-art DRL and can effectively avoid obstacles. When used with UWB beacons, the proposed strategy is suitable for environments with dynamic pedestrians. We also designed a handle device with an audio interface that enables BVI users to interact with the guiding robot through intuitive feedback. The UWB beacons were installed with an audio interface to obtain environmental information. The on-handle and on-beacon verbal feedback provides points of interests and turn-by-turn information to BVI users. BVI users were recruited in this study to conduct navigation tasks in different scenarios. A route was designed in a simulated ward to represent daily activities. In real-world situations, SLAM-based state estimation might be affected by dynamic obstacles, and the visual-based trail may suffer from occlusions from pedestrians or other obstacles. The proposed system successfully navigated through environments with dynamic pedestrians, in which systems based on existing SLAM algorithms have failed.

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“…A ranging error model was then modified to implement PDR and UWB fusion using PF [ 30 ] to mitigate interference of NLoS. Cao et al [ 31 ] designed a UWB ranging and IMU fusion algorithm which used UWB ranging and heading (provided by IMU) to calculate target speed, and an extended Kalman filter to fuse IMU and UWB ranging constricted by estimated speed. Li et al [ 32 ] used an extended Kalman filter to fuse a UWB localization system (not ranging) and IMU, and they also discussed the fusion system under LoS and NLoS environments.…”

Section: Related Workmentioning

confidence: 99%

A CSI-Based Indoor Positioning System Using Single UWB Ranging Correction

Long

Kong

Zhang

et al. 2021

Sensors

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A fingerprint-based localization system is an economic way to solve an indoor positioning problem. However, the traditional off-line fingerprint collection stage is a time-consuming and laborious process which limits the use of fingerprint-based localization systems. In this paper, based on ubiquitous Wireless Fidelity (Wi-Fi) equipment and a low-cost Ultra-Wideband (UWB) ranging system (with only one UWB anchor), a ready-to-use indoor localization system is proposed to realize long-term and high-accuracy indoor positioning. More specifically, in this system, it is divided into two stages: (1) an initial stage, and (2) a positioning stage. In the initial stage, an Inertial Measure Unit (IMU) is used to calculate the position using Pedestrian Dead Reckon (PDR) algorithm within a preset number of steps, and the location-related fingerprints are collected to train a Convolutional Neural Network (CNN) regression model; simultaneously, in order to make the UWB ranging system adapt to the Non-Line-of-Sight (NLoS) environment, the increments of acceleration and angular velocity in IMU and the increments of single UWB ranging measures are correlated to pre-train a Supported Vector Regression (SVR). After reaching the threshold of time or step number, the system is changed into a positioning stage, and the CNN predicts the position calibrated by corrected UWB ranging. At last, a series of practical experiments are conducted in the real environment; the experiment results show that, due to the corrected UWB ranging measures calibrating the CNN parameters in every positioning period, this system has stable localization results in a comparative long-term range. Additionally, it has the advantages of stability, low cost, anti-noise, etc.

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Accurate position tracking with a single UWB anchor

Cited by 56 publications

References 22 publications

Sensor Information Sharing Using a Producer-Consumer Algorithm on Small Vehicles

Sensor Information Sharing Using a Producer-Consumer Algorithm on Small Vehicles

Assistive Navigation Using Deep Reinforcement Learning Guiding Robot With UWB/Voice Beacons and Semantic Feedbacks for Blind and Visually Impaired People

A CSI-Based Indoor Positioning System Using Single UWB Ranging Correction

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