Foot-mounted inertial navigation made easy

Nilsson, John-Olof; Gupta, Amit; Händel, Peter

doi:10.1109/ipin.2014.7275464

Cited by 140 publications

(89 citation statements)

References 20 publications

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“…5. Similar results have been obtained in previous tests [1,18] and in other independent tests [19] which shows that the heading error dominates and that there is a systematic error that depends on which foot the IMU is mounted on. Resulting trajectory plots from real experiments, similar to the simulations shown in this report, can be found in [1].…”

Section: B Error Model Validation 1) Foot-mounted Ins Error Model Vasupporting

confidence: 90%

“…The INS used for these experiments were not the same as described in II-A. Instead, the INS described in [19] was used, with a custom-made IMU using an array of four collocated IMUs.…”

Section: A Crawl Experimentsmentioning

confidence: 99%

“…Hence, these parameters were chosen based on the assumption that the heading error is significantly reduced by using a dual foot-mounted INS setup, which has been shown to be the case in e.g. [1,9,19]. These parameter values makes the distance error less dominant for the dual INS setup during a crawling motion and was based on the assumption that a dual INS setup tuned for crawling motion will perform better than the single INS used for the crawl experiment described in section III-A.…”

Section: B Error Model Validation 1) Foot-mounted Ins Error Model Vamentioning

confidence: 99%

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Cooperative localization using a foot-mounted inertial navigation system and ultrawideband ranging

Olsson

Rantakokko

Nygårds

2014

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

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This paper aims to evaluate the performance gains that can be obtained by introducing cooperative localization in an indoor firefighter localization system, through the use of scenariobased simulations. Robust and accurate indoor localization for firefighters is a problem that is not yet resolved. Foot-mounted inertial navigation systems (INS) have been examined for first responder localization, but they have an accumulating position error that grows over time. By using ultrawideband (UWB) ranging between the firefighters and combining range measurements with position and uncertainty estimates from the foot-mounted INS via a cooperative localization approach it is possible to reduce the position error significantly.An error model for the position estimates received from single and dual foot-mounted INS is proposed based on experimental results, and it contains a scaling error which depends on the distance travelled and a heading error which grows linearly over time. The position error for dead-reckoning systems depends on the type of movement. Similarly, an error model for the UWB range measurements was designed where the range measurements experience a bias and variance, which is determined by the number of walls between the transmitter and receiver.By implementing these error models in a scenario-based simulation environment it is possible to evaluate the performance gain of different cooperative localization algorithms. A centralized extended Kalman Filter (EKF) algorithm has been implemented, and the position accuracy and heading improvements are evaluated over a smoke diving operation scenario. The cooperative localization scheme reduces the position errors by up to 70% in a scenario where a three-person smoke diver team performs a search and rescue operation.

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Section: B Error Model Validation 1) Foot-mounted Ins Error Model Vasupporting

confidence: 90%

“…The INS used for these experiments were not the same as described in II-A. Instead, the INS described in [19] was used, with a custom-made IMU using an array of four collocated IMUs.…”

Section: A Crawl Experimentsmentioning

confidence: 99%

Section: B Error Model Validation 1) Foot-mounted Ins Error Model Vamentioning

confidence: 99%

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Cooperative localization using a foot-mounted inertial navigation system and ultrawideband ranging

Olsson

Rantakokko

Nygårds

2014

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

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“…Despite numerous commercialized connected objects for general public or research purposes [8,9], there is no commercialized open object in terms of small-size, lightweight, and easy to use features available to assist real-life scenarios testing. Here is a list of the main needed features:…”

Section: Enabling Real-life Scenarios Testing With a New Ins/pdrmentioning

confidence: 99%

A New PDR Navigation Device for Challenging Urban Environments

Ortiz¹,

Sousa²,

Renaudin³

2017

Journal of Sensors

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The motivations, the design, and some applications of the new Pedestrian Dead Reckoning (PDR) navigation device, ULISS (Ubiquitous Localization with Inertial Sensors and Satellites), are presented in this paper. It is an original device conceived to follow the European recommendation of privacy by design to protect location data which opens new research toward self-contained pedestrian navigation approaches. Its application is presented with an enhanced PDR algorithm to estimate pedestrian's footpaths in an autonomous manner irrespective of the handheld device carrying mode: texting or swinging. An analysis of real-time coding issues toward a demonstrator is also conducted. Indoor experiments, conducted with 3 persons, give a 5.8% mean positioning error over the 3 km travelled distances.

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“…A notable exception to this is foot-mounted PDR [3], [4] where dedicated sensors are mounted to a user's leg or embedded into their shoe. Such solutions work well for professional personnel such as firefighters or first responders where an additional device can be seen as part of their equipment.…”

Section: Introductionmentioning

confidence: 99%

IMU and magnetometer modeling for smartphone-based PDR

Hostettler

Särkkä

2016

2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN)

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Abstract-In this paper, IMU and magnetometer models that enable pedestrian dead-reckoning without step detection or zero velocity updates on hand-held devices such as smartphones are proposed. The models are suitable for usage with any standard Bayesian filtering or smoothing technique and thus, do not require customized estimators. The method is evaluated in a real scenario using a dataset of approximately three minutes with a trajectory length of 302 m. It is found that the overall shape of the estimated trajectory matches well with the GPS reference trajectory with an estimated trajectory length of 293 m. Some problems in the heading estimation are observed.

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Foot-mounted inertial navigation made easy

Cited by 140 publications

References 20 publications

Cooperative localization using a foot-mounted inertial navigation system and ultrawideband ranging

Cooperative localization using a foot-mounted inertial navigation system and ultrawideband ranging

A New PDR Navigation Device for Challenging Urban Environments

IMU and magnetometer modeling for smartphone-based PDR

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