Fault detection in autonomous robots based on fault injection and learning

In this paper, we study a new approach to fault detection for autonomous robots. Our hypothesis is that hardware faults change the flow of sensory data and the actions performed by the control program. By detecting these changes, the presence of faults can be inferred. In order to test our hypothesis, we collect data from three different tasks performed by real robots. During a number of training runs, we record sensory data from the robots while they are operating normally and after a fault has been injected. We use back-propagation neural networks to synthesize fault detection components based on the data collected in the training runs. We evaluate the performance of the trained fault detectors in terms of number of false positives and time it takes to detect a fault. The results show that good fault detectors can be obtained. We extend the set of possible faults and go on to show that a single fault detector can be trained to detect several faults in both a robot’s sensors and actuators. We show that fault detectors can be synthesized that are robust to variations in the task, and we show how a fault detector can be trained to allow one robot to detect faults that occur in another robot.

Parallelized egocentric fields for autonomous navigation

In this paper, we propose a general framework for local path-planning and steering that can be easily extended to perform high-level behaviors. Our framework is based on the concept of affordances: the possible ways an agent can interact with its environment. Each agent perceives the environment through a set of vector and scalar fields that are represented in the agent’s local space. This egocentric property allows us to efficiently compute a local space-time plan and has better parallel scalability than a global fields approach. We then use these perception fields to compute a fitness measure for every possible action, defined as an affordance field. The action that has the optimal value in the affordance field is the agent’s steering decision. We propose an extension to a linear space-time prediction model for dynamic collision avoidance and present our parallelization results on multicore systems. We analyze and evaluate our framework using a comprehensive suite of test cases provided in SteerBench and demonstrate autonomous virtual pedestrians that perform steering and path planning in unknown environments along with the emergence of high-level responses to never seen before situations.     

Mechanical and Microstructural Characteristics of Superplastic Al-4.42Mg Aluminum Alloy

Abstract： The superplastic response of commercial 5083 alloy （Al-4. 42Mg） under uniaxial tension at strain rates ranging from 5 × 10-5 to 10-2s -1 in the temperature interval 400 -550℃ was systematically studied in this paper. The tension test was conducted on samples of rolling direction. The maximum elongation-to-failure of 486% was found at 500 % and strain rate of 10-4s-1. To identify the main characteristics of superplastic deformation and to determine the mechanism of superplastic deformation of the alloy, the microstructure and fracture of the alloy were analyzed as a function of strain, strain rate and temperature using optical microscopy （OM） and scanning electron microscopy （SEM）, the apparent strain rate sensitivity exponent ma and the apparent activation energy Qa were also studied. Based on the fracture analysis and the calculated data of m and Qa, it is suggested that the dominant deformation mechanism in the present alloy is grain boundary sliding （GBS） during the best deformation condition.     

Gelatin nanocomposite films incorporated with magnetic iron oxide nanoparticles for shelf life extension of grapes

Nanocomposite films were obtained by solution casting method from aqueous solution of bovine gelatin with addition of various concentrations of magnetic iron oxide (MIO) nanoparticles (NPs) (5, 10, 15, and 20% w/w of dry gelatin). The incorporation of MIO NPs improved the mechanical and physical properties of the nanocomposites. The increase in concentration of NPs up to 10% improved barrier and mechanical properties which slightly decreased after increasing the concentration beyond that limit due to particle agglomeration. The scanning electron microscopy and X-ray diffraction (XRD) were used to evaluate the morphology and crystalline structure of gelatin nanocomposite films, respectively. Gelatin nanocomposites with 20% w/w NPs exhibited the highest antimicrobial activity against Escherichia coli (7.1 ± 0.085 mm) and Staphylococcus aureus (8.22 ± 1.04 mm). Finally, the potential of gelatin/MIO nanocomposites as packaging material was evaluated to extend the shelf life of grapes. The gelatin/MIO nanocomposites can be used as a replacement to non-biodegradable packaging.     

Thermal,catalytic, antimicrobial,and chelating aspects of phenolic resin and its polychelates with f‐block elements

The polymeric ligand (resin) was synthesized by condensation of 2‐hydroxy‐4‐ethoxybenzophenone with ethane diol in the presence of polyphosphoric acid as a catalyst at 145°C for 10 h. The synthesized resin was used to study its ion exchange efficiency and to synthesize its polychelates with 4f‐block elements. The resin and its polychelates were characterized on the basis of elemental analyses, electronic spectra, magnetic susceptibilities, IR, NMR, and thermogravimetric analyses. The molecular weight was determined using number–average molecular weight (M_n ) by a vapor pressure osmometry (VPO) method. Ion‐exchange studies at various concentrations of different electrolytes, pH, and rate have been carried out for f‐block elements. Antimicrobial activity of all polychelates and catalytic activity of selected polychelates in organic synthesis have been studied. It is observed that resin can be used as an ion‐exchanger and polychelates are found to be an efficient catalysts and antimicrobial agents. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Mechanism of glycine transport in mouse mammary tissue

The mechanism of glycine transport in lactating mouse mammary gland was investigated. Three Na+-dependent systems of glycine transport, distinguished on the basis of their ionic requirement and sensitivity to 2-(methylamino)isobutyric acid (MeAIB), were A (Na+-dependent, MeAIB-sensitive); (Na++Cl-)-dependent, MeAIB-insensitive; and Na+-dependent, Cl--independent, MeAIB-insensitive. These systems were further distinguished on the basis of inhibition analysis and sensitivity to pH of the extracellular medium and preloading mammary tissue with amino acids. The uptake of glycine via the A system (Km 0.53 mM) was inhibited by preloading mammary tissue with alanine, while glycine uptake mediated by the (Na++Cl-)-dependent, MeAIB-insensitive system (Km 0.47 mM) was downregulated by preloading mammary tissue with all amino acids (alanine, sarcosine and histidine) tested. Treatment of mammary tissue with N-ethylmaleimide inhibited the uptake of glycine via both these systems. Decreasing the pH of the extracellular medium inhibited the uptake of glycine via the A system but not the (Na++Cl-)-dependent, MeAIB-insensitive system. On the basis of ionic requirement, system A appears to comprise two components, one dependent on Na+ plus Cl- and the other on Na+ alone. Insulin upregulated the A system-mediated uptake of glycine in pregnant mouse mammary tissue cultured in vitro, while the (Na++Cl-)-dependent, MeAIB-insensitive system remained unaffected.     

Modeling exposure period for solar disinfection (SODIS) under varying turbidity and cloud cover conditions

Solar disinfection (SODIS) is widely practiced all around the world. The process requires variable exposure periods depending upon a number of process parameters (e.g., water turbidity, atmospheric temperature, and cloud cover conditions). This paper describes the development of a mathematical model to estimate required exposure period to achieve Fecal coliforms (FCs) removal for changing process parameters. Daily and hourly solar radiation were estimated and found to be suitable for SODIS application with intensity of 500 W/m² over a period of 3–5 h/day. Randomized SODIS experiments over a period of 3 years were conducted to consider seasonal and weather variations. Six samples each for five levels of turbidity (0, 5, 10, 20, and 30 NTU) were exposed to sunlight under variable cloud cover conditions on different days during the 3-year sampling period. Samples were collected and analyzed for remaining FCs at different intervals in each sampling day. Analysis of variance revealed that turbidity and percent of cloud cover are the most significant process parameters. It was found that FCs die-off in SODIS bottles followed the first-order kinetics. Different data sets were used for the development and calibration of the model. The calibrated model was further verified against the literature. Simple characteristics curves have also been established for practical application at household level to estimate exposure periods. The study revealed a significant difference between the required exposure periods for different turbidity and cloud cover conditions.