Decentralized Target Tracking based on Multi-Robot Cooperative Triangulation

Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.

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.

Field experiments for marine casualty detection with autonomous surface vehicles

In this paper we present a set of field tests for detection of human in the water with an unmanned surface vehicle using infrared and color cameras. These experiments aimed to contribute in the development of victim target tracking and obstacle avoidance for unmanned surface vehicles operating in marine search and rescue missions. This research is integrated in the work conducted in the European FP7 research project Icarus aiming to develop robotic tools for large scale rescue operations. The tests consisted in the use of the ROAZ unmanned surface vehicle equipped with a precision GPS system for localization and both visible spectrum and IR cameras to detect the target. In the experimental setup, the test human target was deployed in the water wearing a life vest and a diver suit (thus having lower temperature signature in the body except hands and head) and was equipped with a GPS logger. Multiple target approaches were performed in order to test the system with different sun incidence relative angles. The experimental setup, detection method and preliminary results from the field trials performed in the summer of 2013 in Sesimbra, Portugal and in La Spezia, Italy are also presented in this work.

Multi-robot cooperative stereo for outdoor scenarios

13th International Conference on Autonomous Robot Systems (Robotica), 2013

Calibration Method for Underwater Visual Ground-Truth System

This work presents an automatic calibration method for a vision based external underwater ground-truth positioning system. These systems are a relevant tool in benchmarking and assessing the quality of research in underwater robotics applications. A stereo vision system can in suitable environments such as test tanks or in clear water conditions provide accurate position with low cost and flexible operation. In this work we present a two step extrinsic camera parameter calibration procedure in order to reduce the setup time and provide accurate results. The proposed method uses a planar homography decomposition in order to determine the relative camera poses and the determination of vanishing points of detected lines in the image to obtain the global pose of the stereo rig in the reference frame. This method was applied to our external vision based ground-truth at the INESC TEC/Robotics test tank. Results are presented in comparison with an precise calibration performed using points obtained from an accurate 3D LIDAR modelling of the environment.

Structured Light System for Underwater Inspection Operations

In this work we propose the development of a stereo SLS system for underwater inspection operations. We demonstrate how to perform a SLS calibration both in dry and underwater environments using two different methods. The proposed methodology is able to achieve quite accurate results, lower than 1 mm in dry environments. We also display a 3D underwater scan of a known object size, a sea scallop, where the system is able to perform a scan with a global error lower than 2% of the object size.

Formation Control Driven by Cooperative Object Tracking

In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.

Simulation Environment for Multi-Robot Cooperative 3D Target Perception

4th International Conference, SIMPAR 2014, Bergamo, Italy, October 20-23, 2014

Detection of Arah1 (a major peanut allergen) in food using an electrochemical gold nanoparticle-coated screen-printed immunosensor

A gold nanoparticle-coated screen-printed carbon electrode was used as the transducer in the development of an electrochemical immunosensor for Ara h 1 (a major peanut allergen) detection in food samples. Gold nanoparticles (average diameter=32 nm) were electrochemically generated on the surface of screen-printed carbon electrodes. Two monoclonal antibodies were used in a sandwich-type immunoassay and the antibody–antigen interaction was electrochemically detected through stripping analysis of enzymatically (using alkaline phosphatase) deposited silver. The total time of the optimized immunoassay was 3 h 50 min. The developed immunosensor allowed the quantification of Ara h 1 between 12.6 and 2000 ng/ml, with a limit of detection of 3.8 ng/ml, and provided precise (RSD <8.7%) and accurate (recovery >96.6%) results. The immunosensor was successfully applied to the analysis of complex food matrices (cookies and chocolate), being able to detect Ara h 1 in samples containing 0.1% of peanut.

A potentiometric magnetic immunoassay for rapid detection of Salmonella typhimurium

Potentiometric detection with homemade polymeric membrane microelectrodes was coupled to a magnetic sandwich immunoassay for Salmonella typhimurium determination. Cadmium and sodium ion selective electrodes were used respectively as indicator and pseudo-reference electrodes and were prepared in pipette tips to allow potentiometric measurements in microliter sample volumes. In the proposed method, the concentration of S. typhimurium was proportional to the amount of cadmium released upon dissolution of a CdS nanoparticle labeled to the secondary detection antibody. The limit of detection was 2 cells per 100 μL. The immunomagnetic assay with potentiometric detection is suitable for sensitive and rapid (average total time per assay of 75 minutes) detection of S. typhimurium in milk samples. The proposed method is easy to perform, safe, sensitive, and low cost and has potential for in situ analysis.

Molecularly imprinted electrochemical sensor for ochratoxin A detection in food samples

A novel electrochemical sensor for ochratoxin A (OTA) detection was fabricated through the modification of a glassy carbon electrode (GCE) with multiwalled carbon nanotubes (MWCNTs) and a molecularly imprinted polymer (MIP). The MWCNTs dramatically promoted the sensitivity of the developed sensor, while polypyrrole (PPy) imprinted with OTA served as the selective recognition element. The imprinted PPy film was prepared by electropolymerization of pyrrole in the presence of OTA as a template molecule via cyclic voltammetry (CV). The electrochemical oxidation of OTA at the developed sensor was investigated by CV and differential pulse voltammetry (DPV). The developed MIP/MWCNT/GCE sensor showed a linear relationship, when using DPV, between peak current intensity and OTA concentration in the range between 0.050 and 1.0 μM, with limits of detection (LOD) and quantification of 0.0041 μM (1.7 μg/L) and 0.014 μM (5.7 μg/L) respectively. With the developed sensor precise results were obtained; relative standard deviations of 4.2% and 7.5% in the evaluation of the repeatability and reproducibility, respectively. The MIP/MWCNT/GCE sensor is simple to fabricate and easy to use and was successfully applied to the determination of OTA in spiked beer and wine samples, with recoveries between 84 and 104%, without the need of a sample pre-treatment step.

Detection of the peanut allergen Ara h 6 in foodstuffs using a voltammetric biosensing approach

A voltammetric biosensor for Ara h 6 (a peanut allergen) detection in food samples was developed. Gold nanoparticle-modified screen-printed carbon electrodes were used to develop a sandwich-type immunoassay using two-monoclonal antibodies. The antibody-antigen interaction was detected through the electrochemical detection of enzymatically deposited silver. The immunosensor presented a linear range between 1 and 100 ng/ml, as well as high precision (inter-day RSD ≤9.8 %) and accuracy (recoveries ≥96.7 %). The detection and quantification limits were 0.27 and 0.88 ng/ml, respectively. It was possible to detect small levels of Ara h 6 in complex food matrices.

Molecularly imprinted sensor for voltammetric detection of norfloxacin

In this work, a norfloxacin selective modified glassy carbon electrode (GCE) based on a molecularly imprinted polymer (MIP) as electrochemical sensor was developed. A suspension of multi-walled carbon nanotubes (MWCNTs) was deposited on the electrode surface. Subsequently, a molecularly imprinted film was prepared by electropolymerization, via cyclic voltammetry of pyrrole (PPy) in the presence of norfloxacin (NFX) as the template molecule. A control electrode (NIP) was also prepared. Scanning electron microscopy (SEM) and cyclic voltammetry in a ferrocyanide solution were performed for morphological and electrochemical characterisation, respectively. Several experimental parameters were studied and optimised. For quantification purposes the MIP/MWCNT/GCE was immersed in NFX solutions for 10 min, and the detection was performed in voltammetric cell by square wave voltammetry. The proposed sensor presented a linear behaviour, between peak current intensity and logarithmic concentration of NFX between 1 × 10−7 and 8 × 10−6 M. The obtained results presented good precision, with a repeatability of 4.3% and reproducibility of 9% and the detection limit was 4.6 × 10−8 M (S/N = 3). The developed sensor displayed good selectivity and operational lifetime, is simple to fabricate and easy to operate and was successfully applied to the analysis of NFX in urine samples.

Estudo Focado no Utilizador de Software Gratuito para Modelação e Visualização 3D Realista

Computação gráfica um campo que tem vindo a crescer bastante nos últimos anos, desde áreas como cinematográficas, dos videojogos, da animação, o avanço tem sido tão grande que a semelhança com a realidade é cada vez maior. Praticamente hoje em dia todos os filmes têm efeitos gerados através de computação gráfica, até simples anúncios de televisão para não falar do realismo dos videojogos de hoje. Este estudo tem como objectivo mostrar duas alternativas no mundo da computação gráfica, como tal, vão ser usados dois programas, Blender e Unreal Engine. O cenário em questão será todo modelado de raiz e será o mesmo nos dois programas. Serão feitos vários renders ao cenário, em ambos os programas usando diferentes materiais, diferentes tipos de iluminação, em tempo real e não de forma a mostrar as várias alternativas possíveis.