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Concept: Automotive navigation system


Implant placement has been widely used in various kinds of surgery. However, accurate intraoperative drilling performance is essential to avoid injury to adjacent structures. Although some commercially-available surgical navigation systems have been approved for clinical applications, these systems are expensive and the source code is not available to researchers. 3D Slicer is a free, open source software platform for the research community of computer-aided surgery. In this study, a loadable module based on Slicer has been developed and validated to support surgical navigation. This research module allows reliable calibration of the surgical drill, point-based registration and surface matching registration, so that the position and orientation of the surgical drill can be tracked and displayed on the computer screen in real time, aiming at reducing risks. In accuracy verification experiments, the mean target registration error (TRE) for point-based and surface-based registration were 0.31±0.06mm and 1.01±0.06mm respectively, which should meet clinical requirements. Both phantom and cadaver experiments demonstrated the feasibility of our surgical navigation software module.

Concepts: Surgery, Research, Java, Source code, Open source, Free software, Open-source software, Automotive navigation system


Screw fixation for unstable pelvic ring fractures is generally performed using the C-arm. However, some studies reported erroneous piercing with screws, nerve injuries, and vessel injuries. Recent studies have reported the efficacy of screw fixations using navigation systems. The purpose of this retrospective study was to investigate the accuracy of screw fixation using the O-arm(®) imaging system and StealthStation(®) navigation system for unstable pelvic ring fractures.

Concepts: Screw, Cultural studies, Imaging, Automotive navigation system, Satellite navigation system, Screw thread


Line scanning cameras, which capture only a single line of pixels, have been increasingly used in ground based mobile or robotic platforms. In applications where it is advantageous to directly georeference the camera data to world coordinates, an accurate estimate of the camera’s 6D pose is required. This paper focuses on the common case where a mobile platform is equipped with a rigidly mounted line scanning camera, whose pose is unknown, and a navigation system providing vehicle body pose estimates. We propose a novel method that estimates the camera’s pose relative to the navigation system. The approach involves imaging and manually labelling a calibration pattern with distinctly identifiable points, triangulating these points from camera and navigation system data and reprojecting them in order to compute a likelihood, which is maximised to estimate the 6D camera pose. Additionally, a Markov Chain Monte Carlo (MCMC) algorithm is used to estimate the uncertainty of the offset. Tested on two different platforms, the method was able to estimate the pose to within 0.06 m/1.05 ∘ and 0.18 m/2.39 ∘ . We also propose several approaches to displaying and interpreting the 6D results in a human readable way.

Concepts: Estimation theory, Monte Carlo, Java, Markov chain, Markov chain Monte Carlo, Monaco, Camera, Automotive navigation system


Challenging environments pose difficulties for terrain navigation, and therefore wearable and multimodal navigation systems have been proposed to overcome these difficulties. Few such navigation systems, however, have been evaluated in field conditions. We evaluated how a multimodal system can aid in navigating in a forest in the context of a military exercise. The system included a head-mounted display, headphones, and a tactile vibrating vest. Visual, auditory, and tactile modalities were tested and evaluated using unimodal, bimodal, and trimodal conditions. Questionnaires, interviews and observations were used to evaluate the advantages and disadvantages of each modality and their multimodal use. The guidance was considered easy to interpret and helpful in navigation. Simplicity of the displayed information was required, which was partially conflicting with the request for having both distance and directional information available.

Concepts: Navigation, Military, Automotive navigation system, Display device, Modality, Display technology, Multimodal interaction


Radiofrequency ablation for liver tumors (liver RFA) is widely performed under ultrasound guidance. However, discriminating between the tumor and the needle is often difficult because of cavitation caused by RFA-induced coagulation. An unclear ultrasound image can lead to complications and tumor residue. Therefore, image-guided navigation systems based on fiducial registration have been developed. Fiducial points are usually set on a patient’s skin. But the use of internal fiducial points can improve the accuracy of navigation. In this study, a new device is introduced to use internal fiducial points using 2D US.

Concepts: Cancer, Tumor, Ultrasound, Automotive navigation system


In this paper, an anti-jamming method, which turns the single objective optimization problem into a multi-objective optimization problem by utilizing 2-norm, is proposed. The proposed jamming suppression method can reduce the wide nulls and wrong nulls problems, which are generated by the common adaptive nulling methods. Therefore a better signal-noise-ratio (SNR) can be achieved, especially when the jammers are close to satellite signals. It can also improve the robustness of the algorithm. The effectiveness of the proposed method is evaluated by simulation and practical outdoor experiments with the GPS L1 band C/A signals. The experimental results show that with the dedicated method, the nulls targeting at the corresponding jammers become narrower and the wrong nulls can be eliminated.

Concepts: Navigation, Global Positioning System, Automotive navigation system, Satellite navigation system, Global navigation satellite system, GPS, Geodesy, Differential GPS


The Kalman filter has been widely applied in the field of dynamic navigation and positioning. However, its performance will be degraded in the presence of significant model errors and uncertain interferences. In the literature, the fading filter was proposed to control the influences of the model errors, and the H-infinity filter can be adopted to address the uncertainties by minimizing the estimation error in the worst case. In this paper, a new multiple fading factor, suitable for the Global Positioning System (GPS) and the Inertial Navigation System (INS) integrated navigation system, is proposed based on the optimization of the filter, and a comprehensive filtering algorithm is constructed by integrating the advantages of the H-infinity filter and the proposed multiple fading filter. Measurement data of the GPS/INS integrated navigation system are collected under actual conditions. Stability and robustness of the proposed filtering algorithm are tested with various experiments and contrastive analysis are performed with the measurement data. Results demonstrate that both the filter divergence and the influences of outliers are restrained effectively with the proposed filtering algorithm, and precision of the filtering results are improved simultaneously.

Concepts: Estimation theory, Kalman filter, Global Positioning System, Dead reckoning, Automotive navigation system, GPS, Navigational equipment, Korean Air Lines Flight 007


Pulmonary veins isolation (PVI) by radiofrequency (RF) ablation is currently an established treatment for symptomatic, drug-resistant paroxysmal atrial fibrillation. Although the effectiveness of the therapy has been clearly demonstrated, success rate after a single procedure is still sub-optimal. The main reason for recurrences after PVI is electrical pulmonary vein-atrium reconnection. In order to increase the likelihood of permanent PVI, the creation of a transmural, durable lesion is mandatory. The main determinants of lesion size and transmurality are power, stability, duration and contact-force during RF application. In recent times, catheters with contact-force sensors have been developed and released for clinical use. Areas covered: The present review summarizes rational and clinical evidences for efficacy and safety of contact force (CF) technology integrated into 3D navigation systems for AF ablation. Expert commentary Although CF technology has a strong rational, clinical data on the superior safety and efficacy of CF technology over traditional non-CF catheters are still conflicting. The reason for that is very likely to rely on the lack of definite data on how to optimize CF parameters and how to integrate CF data with power, duration of RF applications and information on catheter stability.

Concepts: Time, Blood, Heart, Atrial fibrillation, Effectiveness, Integral, Atrial flutter, Automotive navigation system


The development of the Internet of Things (IoT) has accelerated research in indoor navigation systems, a majority of which rely on adequate wireless signals and sources. Nonetheless, deploying such a system requires periodic site-survey, which is time consuming and labor intensive. To address this issue, in this paper we present Canoe, an indoor navigation system that considers shopping mall scenarios. In our system, we do not assume any prior knowledge, such as floor-plan or the shop locations, access point placement or power settings, historical RSS measurements or fingerprints, etc. Instead, Canoe requires only that the shop owners collect and publish RSS values at the entrances of their shops and can direct a consumer to any of these shops by comparing the observed RSS values. The locations of the consumers and the shops are estimated using maximum likelihood estimation. In doing this, the direction of the target shop relative to the current orientation of the consumer can be precisely computed, such that the direction that a consumer should move can be determined. We have conducted extensive simulations using a real-world dataset. Our experiments in a real shopping mall demonstrate that if 50% of the shops publish their RSS values, Canoe can precisely navigate a consumer within 30 s, with an error rate below 9%.

Concepts: Statistics, Estimation theory, Maximum likelihood, Likelihood function, Automotive navigation system


Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance.

Concepts: Experiment, Inertial navigation system, Doppler effect, Dead reckoning, Sonar, Automotive navigation system, Rocket, Submarine