Developing sensorized arm skin for an octopus inspired robot

Soft skin artefacts made of knitted nylon reinforced silicon rubber were fabricated mimicking octopus skin. A combination of ecoflex 0030 and 0010 were used as matrix of the composite to obtain the right stiffness for the skin artefacts. Material properties were characterised using static uniaxial tension and scissors cutting tests. Two types of tactile sensors were developed to detect normal contact; one used quantum tunnelling composite materials and the second was fabricated from silicone rubber and a conductive textile. Sensitivities of the sensors were tested by applying different modes of loading and the soft sensors were incorporated into the skin prototype. Passive suckers were developed and tested against squid suckers. An integrated skin prototype with embedded deformable sensors and attached suckers developed for the arm of an octopus inspired robot is also presented.

Kinematical analysis of redundant drive wire mechanisms with velocity constraint

In this paper, we propose a new velocity constraint type for Redundant Drive Wire Mechanisms. The purpose of this paper is to demonstrate that the proposed velocity constraint module can fix the orientation of the movable part and to use the kinematical analysis method to obtain the moving direction of the movable part. First, we discuss the necessity of using this velocity constraint type and the possible applications of the proposed mechanism. Second, we derive the basic equations of a wire mechanism with this constraint type. Next, we present a method of motion analysis on active and passive constraint spaces, which is used to find the moving direction of a movable part. Finally, we apply the above analysis method on a wire mechanism with a velocity constraint module and on a wire mechanism with four double actuator modules. By evaluating the results, we prove the validity of the proposed constraint type.

Software-based study of a non-sorting method for median calculation on a set of integer numbers

This paper presents a software-based study of a hardware-based non-sorting median calculation method on a set of integer numbers. The method divides the binary representation of each integer element in the set into bit slices in order to find the element located in the middle position. The method exhibits a linear complexity order and our analysis shows that the best performance in execution time is obtained when slices of 4-bit in size are used for 8-bit and 16-bit integers, in mostly any data set size. Results suggest that software implementation of bit slice method for median calculation outperforms sorting-based methods with increasing improvement for larger data set size. For data set sizes of N > 5, our simulations show an improvement of at least 40%.

Spectrophotometric determination of phosphite in fertilizers in a flow injection system with online sample preparation

A flow injection system with online sample preparation is proposed for the determination of phosphite in liquid fertilizers by spectrophotometry. After loop-based injection, phosphite is oxidized by an acidic permanganate solution (1.0 10(-2) mol L-1 KMnO4 + 1.0 mol L-1 H2SO4) in a heated reactor (50 degreesC). The phosphate generated is then determined by the molybdenum blue method. Influence of flow rates, temperature, and concentration and order of addition of reagents, sample volume, and reactor configuration for the blue complex formation on recorded signals were investigated. The pow system was applied to phosphite determination in commercial samples of liquid fertilizers. The proposed system handles about 80 samples per hour [0.05-0.40% (w/v) H3PO3; R = 0,9998], consuming about 80 muL sample, 1 mg KMnO4, 25 mg (NH)(6)Mo7O24, and Ia mg ascorbic acid per determination. Results are precise [relative standard deviation less than or equal to 3.5% for 0.1% (w/v) H3PO3, n = 12] and in agreement with those obtained by gravimetry at 95% confidence level. (C) 2000 John Wiley & Sons, Inc.

Use of FIA systems for on-line dilution in multielement determination by ICP-MS

A flow-injection (FI) system to match concentrations was used as an auto-diluter in multielement determination by inductively coupled plasma-mass spectrometry (ICP-MS). The flow system comprised loop-based injection or a timed valve that introduced a variable sample volume info a spray chamber through a standard Meinhard nebulizer of an ICP-MS. Routinely analyzed samples such as water, plant, and steel were selected. The accuracy of multielement determination was checked against water standard reference material from the National Institute of Standards and Technology (1643d), plant standard reference material from the National Bureau of Standards (1572 citrus leaves), and steel standard reference material from the National Bureau of Standards (AISI 4340). The measuring system was calibrated with a multielement solution, yielding a linear plot with good precision [relative standard deviation (RSD) < 3%, n = 12]. The results were in agreement at a 95% confidence level with the certified values for the reference materials and also with those obtained by continuous aspiration and by (FI) with a discrete volume. (C) 1999 John Wiley & Sons, Inc.

Conception of wheeled mobile robots with reconfigurable control using integrate prototyping

With the fast innovation of the hardware and software technologies using rapid prototyping devices, with application in the robotics and automation, more and more it becomes necessary the development of applications based on methodologies that facilitate future modifications, updates and enhancements in the original projected system. This paper presents a conception of mobile robots using rapid prototyping, distributing the several control actions in growing levels of complexity and using resources of reconfigurable computing proposal oriented to embed systems implementation. Software and the hardware are structuralized in independents blocks, with connection through common bus. The study and applications of new structures control that permits good performance in relation to the parameter variations. This kind of controller can be tested on different platform representing the wheeled mobile robots using reprogrammable logic components (FPGA). © 2006 IEEE.

Robot-aided neurorehabilitation of the upper extremities

Task-oriented repetitive movements can improve muscle strength and movement co-ordination in patients with impairments due to neurological lesions. The application of robotics and automation technology can serve to assist, enhance, evaluate and document the rehabilitation of movements. The paper provides an overview of existing devices that can support movement therapy of the upper extremities in subjects with neurological pathologies. The devices are critically compared with respect to technical function, clinical applicability, and, if they exist, clinical outcomes.

Cooperative Task Execution between Modular Robots Based on Tight-Loose Cooperation Strategies

The complexity in the execution of cooperative tasks is high due to the fact that a robot team requires movement coordination at the beginning of the mission and continuous coordination during the execution of the task. A variety of techniques have been proposed to give a solution to this problem assuming standard mobile robots. This work focuses on presenting the execution of a cooperative task by a modular robot team. The complexity of the task execution increases due to the fact that each robot is composed of modules which have to be coordinated in a proper way to successfully work. A combined tight and loose cooperation strategy is presented and a bar-pushing example is used as a cooperative task to show the performance of this type of system.

The reviewing process: validating results

Any scientific publication aims to advance the field of knowledge that it deals with, and therefore the editorial staff will always be seeking the most revolutionary papers among all of those received. On the other hand, the reviewers’ task is usually a much more conservative one, as reviewers are responsible for verifying the realism of the methods proposed and the veracity of the claimed results.

Multisensor data fusion for accurate modelling of mobile objects

In the last decade, multi-sensor data fusion has become a broadly demanded discipline to achieve advanced solutions that can be applied in many real world situations, either civil or military. In Defence,accurate detection of all target objects is fundamental to maintaining situational awareness, to locating threats in the battlefield and to identifying and protecting strategically own forces. Civil applications, such as traffic monitoring, have similar requirements in terms of object detection and reliable identification of incidents in order to ensure safety of road users. Thanks to the appropriate data fusion technique, we can give these systems the power to exploit automatically all relevant information from multiple sources to face for instance mission needs or assess daily supervision operations. This paper focuses on its application to active vehicle monitoring in a particular area of high density traffic, and how it is redirecting the research activities being carried out in the computer vision, signal processing and machine learning fields for improving the effectiveness of detection and tracking in ground surveillance scenarios in general. Specifically, our system proposes fusion of data at a feature level which is extracted from a video camera and a laser scanner. In addition, a stochastic-based tracking which introduces some particle filters into the model to deal with uncertainty due to occlusions and improve the previous detection output is presented in this paper. It has been shown that this computer vision tracker contributes to detect objects even under poor visual information. Finally, in the same way that humans are able to analyze both temporal and spatial relations among items in the scene to associate them a meaning, once the targets objects have been correctly detected and tracked, it is desired that machines can provide a trustworthy description of what is happening in the scene under surveillance. Accomplishing so ambitious task requires a machine learning-based hierarchic architecture able to extract and analyse behaviours at different abstraction levels. A real experimental testbed has been implemented for the evaluation of the proposed modular system. Such scenario is a closed circuit where real traffic situations can be simulated. First results have shown the strength of the proposed system.