Scenario-based evaluations of high-accuracy personal positioning systems

Rantakokko, Jouni; Emilsson, Erika; Strömbäck, Peter; Rydell, Joakim

doi:10.1109/plans.2012.6236871

Cited by 10 publications

(13 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1. In the prototype implementation the ZUPT-aided foot-mounted INS in [7] is used, together with the FUNCube Dongle Pro+ radio receiver [31] and an omnidirectional antenna. A position estimate is extracted every time a ZUPT is registered in the footmounted INS, however only those in time with incoming RSS fingerprints are used to perform the DP-SLAM time updates.…”

Section: A Implementation Detailsmentioning

confidence: 99%

See 1 more Smart Citation

Indoor positioning using multi-frequency RSS with foot-mounted INS

Nilsson

Rantakokko

Skoglund

et al. 2014

2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN)

View full text Add to dashboard Cite

Abstract-This paper presents a system which combines a zero-velocity-update-(ZUPT-)aided inertial navigation system (INS), using a foot-mounted inertial measurement unit (IMU), with opportunistic use of multi-frequency received signal strength (RSS) measurements. The system does not rely on maps or pre-collected data from surveys of the radio-frequency (RF) environment. Instead it builds its own database of collected RSS measurements during the course of the operation. New RSS measurements are continuously compared with the stored values in the database, and when the user returns to a previously visited area this can thus be detected. This enables loop-closures to be detected online and used for error drift correction. The system utilises a distributed particle simultaneous localization and mapping (DP-SLAM) algorithm which provides a flexible 2D navigation platform that can be extended with more sensors. The experimental results presented in this paper indicates that the developed RSS SLAM algorithm can, in many cases, significantly improve the positioning performance of a foot-mounted INS.

show abstract

Section: A Implementation Detailsmentioning

confidence: 99%

“…An early example using shoe-mounted inertial and magnetic sensors was presented in [4], and since then several similar systems have been developed [2,[5][6][7][8]. The key idea is to detect and utilize the stand-still phase of the foot during each gait cycle in a zerovelocity-update (ZUPT).…”

Section: Introductionmentioning

confidence: 99%

Indoor positioning using multi-frequency RSS with foot-mounted INS

Nilsson

Rantakokko

Skoglund

et al. 2014

2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN)

View full text Add to dashboard Cite

show abstract

“…Recent approaches aim to improve zero-velocity detection during common motions by implementing adaptive techniques that are dependent on velocity [2], [3] or gait frequency [4]. However, modelling zero-velocity detection during motions such as stair climbing and crawling, while maintaining accurate midstance detection during walking and running, is fundamentally challenging [5]. In past work [6], we showed that motion classification can be useful when combined with a series of motion-specific detectors, as this allows each detector to be optimized for a particular motion type.…”

Section: Introductionmentioning

confidence: 99%

LSTM-Based Zero-Velocity Detection for Robust Inertial Navigation

Wagstaff

Kelly

2018

2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN)

108

View full text Add to dashboard Cite

We present a method to improve the accuracy of a zero-velocity-aided inertial navigation system (INS) by replacing the standard zero-velocity detector with a long short-term memory (LSTM) neural network. While existing threshold-based zero-velocity detectors are not robust to varying motion types, our learned model accurately detects stationary periods of the inertial measurement unit (IMU) despite changes in the motion of the user. Upon detection, zero-velocity pseudo-measurements are fused with a dead reckoning motion model in an extended Kalman filter (EKF). We demonstrate that our LSTM-based zero-velocity detector, used within a zero-velocity-aided INS, improves zero-velocity detection during human localization tasks. Consequently, localization accuracy is also improved.Our system is evaluated on more than 7.5 km of indoor pedestrian locomotion data, acquired from five different subjects. We show that 3D positioning error is reduced by over 34% compared to existing fixed-threshold zero-velocity detectors for walking, running, and stair climbing motions. Additionally, we demonstrate how our learned zero-velocity detector operates effectively during crawling and ladder climbing. Our system is calibration-free (no careful threshold-tuning is required) and operates consistently with differing users, IMU placements, and shoe types, while being compatible with any generic zero-velocityaided INS.

show abstract

“…Scenario-based tests are expected to play an important role in the performance evaluations of firefighter positioning systems [21][22][23], since this ensures that the test subjects use realistic movements and distances between (and number of) firefighters. The former affects the performance of the footmounted INS, especially in operations with heavy smoke and heat that forces the firefighters to move close to the ground.…”

Section: Introductionmentioning

confidence: 99%

Accurate indoor positioning of firefighters using dual foot-mounted inertial sensors and inter-agent ranging

Nilsson

Rantakokko

Händel

et al. 2014

2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014

Self Cite

View full text Add to dashboard Cite

-A real-time cooperative localization system, utilizing dual foot-mounted low-cost inertial sensors and RFbased inter-agent ranging, has been developed. Scenario-based tests have been performed, using fully-equipped firefighters mimicking a search operation in a partly smoke-filled environment, to evaluate the performance of the TOR (Tactical lOcatoR) system. The performed tests included realistic firefighter movements and inter-agent distances, factors that are crucial in order to provide realistic evaluations of the expected performance in real-world operations. The tests indicate that the TOR system may be able to provide a position accuracy of approximately two to three meters during realistic firefighter operations, with only two smoke diving firefighters and one supervising firefighter within range.

show abstract

Scenario-based evaluations of high-accuracy personal positioning systems

Cited by 10 publications

References 7 publications

Indoor positioning using multi-frequency RSS with foot-mounted INS

Indoor positioning using multi-frequency RSS with foot-mounted INS

LSTM-Based Zero-Velocity Detection for Robust Inertial Navigation

Accurate indoor positioning of firefighters using dual foot-mounted inertial sensors and inter-agent ranging

Contact Info

Product

Resources

About