Localization system for pedestrians based on sensor and information fusion

Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device's GPS chip. This means that in indoor or in more dense environments these applications don't work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.

Application of Visual-Inertial SLAM for 3D Mapping of Underground Environments

The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.

Biomimetic norfloxacin sensors made of molecularly-imprinted materials for potentiometric transduction

A biomimetic sensor for norfloxacin is presented that is based on host-guest interactions and potentiometric transduction. The artificial host was imprinted into polymers made from methacrylic acid and/or 2-vinyl pyridine. The resulting particles were entrapped in a plasticized poly(vinyl chloride) (PVC) matrix. The sensors exhibit near-Nernstian response in steady state evaluations, and detection limits range from 0.40 to 1.0 μgmL−1, respectively, and are independent of pH values at between 2 and 6, and 8 and 11, respectively. Good selectivity was observed over several potential interferents. In flowing media, the sensors exhibit fast response, a sensitivity of 68.2 mV per decade, a linear range from 79 μM to 2.5 mM, a detection limit of 20 μgmL−1, and a stable baseline. The sensors were successfully applied to field monitoring of norfloxacin in fish samples, biological samples, and pharmaceutical products

Biomimetic sensors of molecularly-imprinted polymers for chlorpromazine determination

A new man-tailored biomimetic sensor for Chlorpromazine host-guest interactions and potentiometric transduction is presented. The artificial host was imprinted within methacrylic acid, 2-vinyl pyridine and 2-acrylamido-2-methyl-1-propanesulfonic acid based polymers. Molecularly imprinted particles were dispersed in 2-nitrophenyloctyl ether and entrapped in a poly(vinyl chloride) matrix. Slopes and detection limits ranged 51–67 mV/decade and 0.46–3.9 μg/mL, respectively, in steady state conditions. Sensors were independent fromthe pHof test solutionswithin 2.0–5.5.Good selectivitywas observed towards oxytetracycline, doxytetracycline, ciprofloxacin, enrofloxacin, nalidixic acid, sulfadiazine, trimethoprim, glycine, hydroxylamine, cysteine and creatinine. Analytical features in flowing media were evaluated on a double-channel manifold, with a carrier solution of 5.0×10−2 mol/L phosphate buffer. Near-Nernstian response was observed over the concentration range 1.0×10−4 to 1.0×10−2 mol/L. Average slopes were about 48 mV/decade. The sensors were successfully applied to field monitoring of CPZ in fish samples, offering the advantages of simplicity, accuracy, automation feasibility and applicability to complex samples.

Smart object for 3D interaction

This paper reports on the creation of an interface for 3D virtual environments, computer-aided design applications or computer games. Standard computer interfaces are bound to 2D surfaces, e.g., computer mouses, keyboards, touch pads or touch screens. The Smart Object is intended to provide the user with a 3D interface by using sensors that register movement (inertial measurement unit), touch (touch screen) and voice (microphone). The design and development process as well as the tests and results are presented in this paper. The Smart Object was developed by a team of four third-year engineering students from diverse scientific backgrounds and nationalities during one semester.

Traveled Distance Estimation Algorithm for Indoor Localization

This paper presents an ankle mounted Inertial Navigation System (INS) used to estimate the distance traveled by a pedestrian. This distance is estimated by the number of steps given by the user. The proposed method is based on force sensors to enhance the results obtained from an INS. Experimental results have shown that, depending on the step frequency, the traveled distance error varies between 2.7% and 5.6%.

Person Localization Using Sensor Information Fusion

Nowadays the incredible grow of mobile devices market led to the need for location-aware applications. However, sometimes person location is difficult to obtain, since most of these devices only have a GPS (Global Positioning System) chip to retrieve location. In order to suppress this limitation and to provide location everywhere (even where a structured environment doesn’t exist) a wearable inertial navigation system is proposed, which is a convenient way to track people in situations where other localization systems fail. The system combines pedestrian dead reckoning with GPS, using widely available, low-cost and low-power hardware components. The system innovation is the information fusion and the use of probabilistic methods to learn persons gait behavior to correct, in real-time, the drift errors given by the sensors.

Biomimetic sensors of molecularly-imprinted polymers for chlorpromazine determination

A new man-tailored biomimetic sensor for Chlorpromazine host-guest interactions and potentiometric transduction is presented. The artificial host was imprinted within methacrylic acid, 2-vinyl pyridine and 2-acrylamido-2-methyl-1-propanesulfonic acid based polymers. Molecularly imprinted particles were dispersed in 2-nitrophenyloctyl ether and entrapped in a poly(vinyl chloride) matrix. Slopes and detection limits ranged 51–67 mV/decade and 0.46–3.9 μg/mL, respectively, in steady state conditions. Sensors were independent from the pH of test solutions within 2.0–5.5. Good selectivity was observed towards oxytetracycline, doxytetracycline, ciprofloxacin, enrofloxacin, nalidixic acid, sulfadiazine, trimethoprim, glycine, hydroxylamine, cysteine and creatinine. Analytical features in flowing media were evaluated on a double-channel manifold, with a carrier solution of 5.0 × 10−2 mol/L phosphate buffer. Near-Nernstian response was observed over the concentration range 1.0 × 10−4 to 1.0 × 10−2 mol/L. Average slopes were about 48 mV/decade. The sensors were successfully applied to field monitoring of CPZ in fish samples, offering the advantages of simplicity, accuracy, automation feasibility and applicability to complex samples.

Biomimetic norfloxacin sensors made of molecularly-imprinted materials for potentiometric transduction

A biomimetic sensor for norfloxacin is presented that is based on host-guest interactions and potentiometric transduction. The artificial host was imprinted into polymers made from methacrylic acid and/or 2-vinyl pyridine. The resulting particles were entrapped in a plasticized poly(vinyl chloride) (PVC) matrix. The sensors exhibit near-Nernstian response in steady state evaluations, and detection limits range from 0.40 to 1.0 μg mL−1, respectively, and are independent of pH values at between 2 and 6, and 8 and 11, respectively. Good selectivity was observed over several potential interferents. In flowing media, the sensors exhibit fast response, a sensitivity of 68.2 mV per decade, a linear range from 79 μM to 2.5 mM, a detection limit of 20 μg mL−1, and a stable baseline. The sensors were successfully applied to field monitoring of norfloxacin in fish samples, biological samples, and pharmaceutical products.

Autonomous Surface Vehicle Docking Manoeuvre with Visual Information

This work presents a hybrid coordinated manoeuvre for docking an autonomous surface vehicle with an autonomous underwater vehicle. The control manoeuvre uses visual information to estimate the AUV relative position and attitude in relation to the ASV and steers the ASV in order to dock with the AUV. The AUV is assumed to be at surface with only a small fraction of its volume visible. The system implemented in the autonomous surface vehicle ROAZ, developed by LSA-ISEP to perform missions in river environment, test autonomous AUV docking capabilities and multiple AUV/ASV coordinated missions is presented. Information from a low cost embedded robotics vision system (LSAVision), along with inertial navigation sensors is fused in an extended Kalman filter and used to determine AUV relative position and orientation to the surface vehicle The real time vision processing system is described and results are presented in operational scenario.