Temporal calibration in multisensor tracking setups

Huber, Manuel; Schlegel, Michael; Klinker, Gudrun

doi:10.1109/ismar.2009.5336465

Cited by 12 publications

(10 citation statements)

References 6 publications

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“…Based on (24), and by re-applying linearisation of the process function about the state-vector estimate and discretisation [42], the state-transition matrix modifies as:…”

Section: A Improved Gnss/uwb Model For Ekf-based Time-offset Calibrationmentioning

confidence: 99%

Enhanced EKF-Based Time Calibration for GNSS/UWB Tight Integration

et al. 2023

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Tight integration of low-cost Ultra-Wide Band (UWB) ranging sensors with mass-market Global Navigation Satellite System (GNSS) receivers is gaining attention as a high-accuracy positioning strategy for consumer applications dealing with challenging environments. However, due to independent clocks embedded in Commercial-Off-The-Shelf (COTS) chipsets, the time scales associated with sensor measurements are misaligned, leading to inconsistent data fusion. Centralized, recursive filtering architectures can compensate for this offset and achieve accurate state estimation. In line with this, a GNSS/UWB tight integration scheme based on an Extended Kalman Filter (EKF) is developed that performs online time calibration of the sensors' measurements by recursively modeling the GNSS/UWB time-offset as an additional unknown in the system state-space model. Furthermore, a double-update filtering model is proposed that embeds optimizations for the adaptive weighting of UWB measurements. Simulation results show that the double-update EKF algorithm can achieve a horizontal positioning accuracy gain of 41.60 % over a plain EKF integration with uncalibrated time-offset and of 15.43 % over the EKF with naive time-offset calibration. Moreover, a real-world experimental assessment demonstrates improved Root-Mean-Square Error (RMSE) performance of 57.58 % and 31.03 %, respectively.

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“…Based on (24), and by re-applying linearisation of the process function about the state-vector estimate and discretisation [42], the state-transition matrix modifies as:…”

Section: A Improved Gnss/uwb Model For Ekf-based Time-offset Calibrationmentioning

confidence: 99%

Enhanced EKF-Based Time Calibration for GNSS/UWB Tight Integration

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Due to the nature of multi-modal sensing, temporal calibration is essential to ensure reliable data. The crosscorrelation method was applied to determine the lag between two streams of signals by finding the maximum peak of the sliding dot product [14], [15]. The four sensors were matched by three pairs: FingerTPS and Leap Motion, Leap Motion and trakSTAR, trakSTAR and IR emitter/detector.…”

Section: B Signal Filtering and Temporal Synchronizationmentioning

confidence: 99%

A Method for Segmenting the Process of Needle Insertion during Simulated Cannulation using Sensor Data

Liu

Petersen

Zhang

et al. 2020

2020 42nd Annual International Conference of the IEEE Engineering in Medicine &Amp; Biology Society (EMBC)

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Cannulation is a routine yet challenging medical procedure resulting in a direct impact on patient outcomes. While current training programs provide guidelines to learn this complex procedure, the lack of objective and quantitative feedback impedes learning this skill more effectively. In this paper, we present a simulator for performing hemodialysis cannulation that captures the process using multiple sensing modalities that provide a multi-faceted assessment of cannulation. Further, we describe an algorithm towards segmenting the cannulation process using specific events in the sensor data for detailed analysis. Results from three participants with varying levels of clinical cannulation expertise are presented along with a metric that successfully differentiates the three participants. This work could lead to sensor-based cannulation skill assessment and training in the future potentially resulting in improved patient outcomes.

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“…It is worth noting that in the case of different sensor frame rates, the slower sensor should be chosen as the anchor to reduce the interpolation errors [27]. Finally, after the time delay optimization, we form a list of state correspondences between the states at measurement times 1 T of the anchor sensor, and corresponding interpolated times of the second sensor, 2 T , defined as…”

Section: B Temporal Calibrationmentioning

confidence: 99%

Spatio-Temporal Multisensor Calibration Based on Gaussian Processes Moving Object Tracking

Peršić,

Petrović,

Marković

et al. 2019

Preprint

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Perception is one of the key abilities of autonomous mobile robotic systems, which often relies on fusion of heterogeneous sensors. Although this heterogeneity presents a challenge for sensor calibration, it is also the main prospect for reliability and robustness of autonomous systems. In this paper, we propose a method for multisensor calibration based on Gaussian processes (GPs) estimated moving object trajectories, resulting with temporal and extrinsic parameters. The appealing properties of the proposed temporal calibration method are: coordinate frame invariance, thus avoiding prior extrinsic calibration, theoretically grounded batch state estimation and interpolation using GPs, computational efficiency with O(n) complexity, leveraging data already available in autonomous robot platforms, and the end result enabling 3D point-to-point extrinsic multisensor calibration. The proposed method is validated both in simulations and real-world experiments. For real-world experiment we evaluated the method on two multisensor systems: an externally triggered stereo camera, thus having temporal ground truth readily available, and a heterogeneous combination of a camera and motion capture system. The results show that the estimated time delays are accurate up to a fraction of the fastest sensor sampling time.

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Temporal calibration in multisensor tracking setups

Cited by 12 publications

References 6 publications

Enhanced EKF-Based Time Calibration for GNSS/UWB Tight Integration

Enhanced EKF-Based Time Calibration for GNSS/UWB Tight Integration

A Method for Segmenting the Process of Needle Insertion during Simulated Cannulation using Sensor Data

Spatio-Temporal Multisensor Calibration Based on Gaussian Processes Moving Object Tracking

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