TORP: The Open Robot Project A Framework for Module-Based Robots

The development of robots has shown itself as a very complex interdisciplinary research field. The predominant procedure for these developments in the last decades is based on the assumption that each robot is a fully personalized project, with the direct embedding of hardware and software technologies in robot parts with no level of abstraction. Although this methodology has brought countless benefits to the robotics research, on the other hand, it has imposed major drawbacks: (i) the difficulty to reuse hardware and software parts in new robots or new versions; (ii) the difficulty to compare performance of different robots parts; and (iii) the difficulty to adapt development needs-in hardware and software levels-to local groups expertise. Large advances might be reached, for example, if physical parts of a robot could be reused in a different robot constructed with other technologies by other researcher or group. This paper proposes a framework for robots, TORP (The Open Robot Project), that aims to put forward a standardization in all dimensions (electrical, mechanical and computational) of a robot shared development model. This architecture is based on the dissociation between the robot and its parts, and between the robot parts and their technologies. In this paper, the first specification for a TORP family and the first humanoid robot constructed following the TORP specification set are presented, as well as the advances proposed for their improvement.

A simple interferometric method to measure the calibration factor and displacement amplification in piezoelectric flextensional actuators

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modeling a spatially restricted distribution in the Neotropics: How the size of calibration area affects the performance of five presence-only methods

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Determination of jet energy calibration and transverse momentum resolution in CMS

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Multivalued adaptive neuro-fuzzy controller for robot vehicle - art. no. 1406

Robotic vehicle navigation in unstructured and uncertain environments is still a challenge. This paper presents the implementation of a multivalued neurofuzzy controller for autonomous ground vehicle (AGVs) in indoor environments. The control system consists of a hierarchy of mobile robot using multivalued adaptive neuro-fuzzy inference system behaviors.

Construction and calibration of permeation tubes.

A dynamic system for stablishing a known standard gas mixture is necessary for many studies such as development and testing of analytical methods. A permeation tube can be used for this purpose. The work described here shows the construction, operation and calibration of a simple permeation tube which can be used to obtain large amounts of a standard gas.

Paraconsistent Autonomous Mobile Robot Emmy III

This work presents some improvements regarding to the autonomous mobile robot Emmy based on Paraconsistent Annotated Evidential Logic ET. A discussion on navigation system is presented.

Comparison of proton energy loss in thick absorbers in terms of a reduced calibration curve

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Calibration of therapeutic ultrasound equipment

Temporal and spatial acoustic intensity (SATA) of therapeutic ultrasound (US) equipment should be monitored periodically. In order to evaluate the conditions of US equipment in use in the city of Piracicaba-Sao Paulo, Brazil, 31 machines - representing all Brazilian manufacturers - were analysed under continuous and pulsed conditions at a frequency of 1 MHz. Data about temporal and spatial acoustic intensity were collected and the use of equipment was surveyed. Intensities of 0.1, 0.2, 0.5, 0.8, 1.0, 1.5, 2.0, 2.5 and 3.0 Wcm -2, indicated on the equipment panel were analysed using a previously calibrated digital radiation pressure scale, model UPM-DT-1 (Ohmic Instruments Co). The acoustic intensity (I) results were expressed as superior and inferior quartile ranges for transducers with metal surfaces of 9 cm 2 and an effective radiation area (ERA) Of 4 cm 2. The results under continuous conditions were: I 0.1 = -20.0% and -96%. I 0.2 = -3.1% and -83.7%. I 0.5 = -35.0% and -86.5%. I 0.8 = -37.5% and -71.0%. I 2.5 = -49.0% and -69.5%. I 3.0 = -58.1% and -77.6%. For pulsed conditions, intensities were: I 0.1 = -40.0% and -86.2%. I 1.0 = -50.0% and -86.5%. I 1.5 = -62.5% and -82.5%. I 2.0 = -62.5% and -81.6%. I 2.5 = -64.7% and -88.8%. I 3.0 = -87.1% and -94.8%. In reply to the questionnaire drawn up to check the conditions of use of equipment, all users reported the use of hydrosoluble gel as a coupling medium and none had carried out previous calibrations. Most users used intensities in the range of 0.4. to 1.0 Wcm -2 and used machines for 300 to 400 minutes per week. The majority of machines had been bought during the previous seven years and weekly use ranged from less than 100 minutes to 700 minutes (11 hours 40 minutes). Findings confirm previous observations of discrepancy between the intensity indicated on the equipment panel and that emitted by the transducer and highlight the necessity for periodic evaluations of US equipment.

Line based camera calibration in machine vision dynamic applications

The problem of dynamic camera calibration considering moving objects in close range environments using straight lines as references is addressed. A mathematical model for the correspondence of a straight line in the object and image spaces is discussed. This model is based on the equivalence between the vector normal to the interpretation plane in the image space and the vector normal to the rotated interpretation plane in the object space. In order to solve the dynamic camera calibration, Kalman Filtering is applied; an iterative process based on the recursive property of the Kalman Filter is defined, using the sequentially estimated camera orientation parameters to feedback the feature extraction process in the image. For the dynamic case, e.g. an image sequence of a moving object, a state prediction and a covariance matrix for the next instant is obtained using the available estimates and the system model. Filtered state estimates can be computed from these predicted estimates using the Kalman Filtering approach and based on the system model parameters with good quality, for each instant of an image sequence. The proposed approach was tested with simulated and real data. Experiments with real data were carried out in a controlled environment, considering a sequence of images of a moving cube in a linear trajectory over a flat surface.

Rapid determination of zinc in foods by flow injection analysis with flame AAS using gradient calibration method

A calibration method was developed using flow injection analysis (FI) with a Gradient Calibration Method (GCM). The method allows the rapid determination of zinc In foods (approximately 30 min) after treatment with concentrated sulphuric acid and 30% hydrogen peroxide, and analysis with flame atomic absorption spectrometry (FAAS). The method provides analytical results with a relative standard deviation of about 2% and requires less time than by conventional FI calibration. The electronic selection of different segments along the gradient and monitoring of the technique covers wide concentration ranges while maintaining the inherent high precision of flow injection analysis. Concentrations, flow rates, and flow times of the reagents were optimized in order to obtain best accuracy and precision. Flow rates of 10 mL/min were selected for zinc. In addition, the system enables electronic dilution and calibration where a multipoint curve can be constructed using a single sample injection.

Calibration uncertainty estimation for internal aerodynamic balance

Aerodynamic balances are employed in wind tunnels to estimate the forces and moments acting on the model under test. This paper proposes a methodology for the assessment of uncertainty in the calibration of an internal multi-component aerodynamic balance. In order to obtain a suitable model to provide aerodynamic loads from the balance sensor responses, a calibration is performed prior to the tests by applying known weights to the balance. A multivariate polynomial fitting by the least squares method is used to interpolate the calibration data points. The uncertainties of both the applied loads and the readings of the sensors are considered in the regression. The data reduction includes the estimation of the calibration coefficients, the predicted values of the load components and their corresponding uncertainties, as well as the goodness of fit.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

Reduced calibration curve for proton computed tomography

The pCT deals with relatively thick targets like the human head or trunk. Thus, the fidelity of pCT as a tool for proton therapy planning depends on the accuracy of physical formulas used for proton interaction with thick absorbers. Although the actual overall accuracy of the proton stopping power in the Bethe-Bloch domain is about 1%, the analytical calculations and the Monte Carlo simulations with codes like TRIM/SRIM, MCNPX and GEANT4 do not agreed with each other. A tentative to validate the codes against experimental data for thick absorbers bring some difficulties: only a few data is available and the existing data sets have been acquired at different initial proton energies, and for different absorber materials. In this work we compare the results of our Monte Carlo simulations with existing experimental data in terms of reduced calibration curve, i.e. the range - energy dependence normalized on the range scale by the full projected CSDA range for given initial proton energy in a given material, taken from the NIST PSTAR database, and on the final proton energy scale - by the given initial energy of protons. This approach is almost energy and material independent. The results of our analysis are important for pCT development because the contradictions observed at arbitrary low initial proton energies could be easily scaled now to typical pCT energies. © 2010 American Institute of Physics.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.