Natural and hybrid bimanual interaction for virtual assembly tasks

This paper focuses on the simulation of bimanual assembly/disassembly operations for training or product design applications. Most assembly applications have been limited to simulate only unimanual tasks or bimanual tasks with one hand. However, recent research has introduced the use of two haptic devices for bimanual assembly. We propose a more natural and low-cost bimanual interaction than existing ones based on Markerless motion capture (Mocap) systems. Specifically, this paper presents two interactions based on a Markerless Mocap technology and one interaction based on combining Markerless Mocap technology with haptic technology. A set of experiments following a within-subjects design have been implemented to test the usability of the proposed interfaces. The Markerless Mocap-based interactions were validated with respect to two-haptic-based interactions, as the latter has been successfully integrated into bimanual assembly simulators. The pure Markerless Mocap interaction proved to be either the most or least efficient depending on the configuration (with 2D or 3D tracking, respectively). Usability results among the proposed interactions and the two-haptic based interaction showed no significant differences. These results suggest that Markerless Mocap or hybrid interactions are valid solutions for simulating bimanual assembly tasks when the precision of the motion is not critical. The decision on which technology to use should depend on the trade-off between the precision requested to simulate the task, the cost, and inner features of the technology.     

A Robot Application for Marine Vessel Inspection

Seagoing vessels have to undergo regular inspections, which are currently performed manually by ship surveyors. The main cost factor in a ship inspection is to provide access to the different areas of the ship, since the surveyor has to be close to the inspected parts, usually within arm's reach, either to perform a visual analysis or to take thickness measurements. The access to the structural elements in cargo holds, e.g., bulkheads, is normally provided by staging or by “cherry‐picking” cranes. To make ship inspections safer and more cost‐efficient, we have introduced new inspection methods, tools, and systems, which have been evaluated in field trials, particularly focusing on cargo holds. More precisely, two magnetic climbing robots and a micro‐aerial vehicle, which are able to assist the surveyor during the inspection, are introduced. Since localization of inspection data is mandatory for the surveyor, we also introduce an external localization system that has been verified in field trials, using a climbing inspection robot. Furthermore, the inspection data collected by the robotic systems are organized and handled by a spatial content management system that enables us to compare the inspection data of one survey with those from another, as well as to document the ship inspection when the robot team is used. Image‐based defect detection is addressed by proposing an integrated solution for detecting corrosion and cracks. The systems' performance is reported, as well as conclusions on their usability, all in accordance with the output of field trials performed onboard two different vessels under real inspection conditions.     

Using genetic algorithms to generate test sequences for complex timed systems

The generation of test data for state-based specifications is a computationally expensive process. This problem is magnified if we consider that time constraints have to be taken into account to govern the transitions of the studied system. The main goal of this paper is to introduce a complete methodology, supported by tools, that addresses this issue by representing the test data generation problem as an optimization problem. We use heuristics to generate test cases. In order to assess the suitability of our approach we consider two different case studies: a communication protocol and the scientific application BIPS3D. We give details concerning how the test case generation problem can be presented as a search problem and automated. Genetic algorithms (GAs) and random search are used to generate test data and evaluate the approach. GAs outperform random search and seem to scale well as the problem size increases. It is worth to mention that we use a very simple fitness function that can be easily adapted to be used with other evolutionary search techniques.     

CAMMInA: a mobile ambient information system to motivate elders to exercise

Several strategies have been identified for designing effective persuasive technology that encourages people to adopt healthy lifestyle habits. However, to implement these strategies for motivating elders to exercise, we need to take into account the elders’ particular characteristics, their needs, and the problems they face to exercise. This paper presents the results of a case study conducted to identify the factors that influence elders to maintain a regular exercise routine. These results enabled us to inform the design of an ambient information system, which by requiring minimal attention and cognitive effort from elders, makes them aware of relevant information that motivates them to exercise. To reach this end, the system implements the following strategies for persuading: abstraction, historical information and reflection, triggers for exercising, and positive and playful reinforcement. A system usability evaluation enabled us to validate these strategies for motivating elders.     

Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles

Identifying the optimal subset of regressors in a regression bagging ensemble is a difficult task that has exponential cost in the size of the ensemble. In this article we analyze two approximate techniques especially devised to address this problem. The first strategy constructs a relaxed version of the problem that can be solved using semidefinite programming. The second one is based on modifying the order of aggregation of the regressors. Ordered aggregation is a simple forward selection algorithm that incorporates at each step the regressor that reduces the training error of the current subensemble the most. Both techniques can be used to identify subensembles that are close to the optimal ones, which can be obtained by exhaustive search at a larger computational cost. Experiments in a wide variety of synthetic and real-world regression problems show that pruned ensembles composed of only 20% of the initial regressors often have better generalization performance than the original bagging ensembles. These improvements are due to a reduction in the bias and the covariance components of the generalization error. Subensembles obtained using either SDP or ordered aggregation generally outperform subensembles obtained by other ensemble pruning methods and ensembles generated by the Adaboost.R2 algorithm, negative correlation learning or regularized linear stacked generalization. Ordered aggregation has a slightly better overall performance than SDP in the problems investigated. However, the difference is not statistically significant. Ordered aggregation has the further advantage that it produces a nested sequence of near-optimal subensembles of increasing size with no additional computational cost.     

A particle filter-based approach for tracking undersea narrow telecommunication cables

The surveillance and inspection of underwater installations such as telecommunication cables are currently carried out by trained operators who, from the surface, guide a remotely operated vehicle (ROV) with cameras mounted over it. This manual visual control is, however, a very tedious job that tends to fail if the operator loses concentration. This paper describes a tracking system for underwater narrow telecommunication cables, the main objective of which is to allow an autonomous underwater vehicle to video-document the whole length of a cable. The approach is based on particle filters (PFs) because of their natural ability to model multi-dimensional multi-modal PDFs, which allows handling in a more appropriate way the ambiguities that naturally arise from undersea environments. In effect, despite the special visual features that artificial objects present, which allow distinguishing them in natural scenarios such as the seabed, distracting background such as rocks or algae growing on top and nearby cables, complicate the detection and tracking and give rise to ambiguities when rocks or marine growth form shapes and textures that resemble the cable. Apart from the different models that a PF requires, the paper also describes a set of added features, which successfully compensate some large errors in the cable pose estimation when the non-enhanced tracker is applied. Extensive experimental results over a test set of more than 10,000 frames, for which a ground truth has been manually generated, have shown the usefulness of the solution proposed. Besides, results for a set of six video sequences accounting for almost 150,000 frames and around one hour and a half of successful continuous video tracking are also discussed. All those images come from inspection runs captured by ROVs navigating over real telecommunication undersea cables.     

Solving complex problems with a bioinspired model

Membrane systems are parallel and bioinspired systems which simulate membranes behavior when processing information. As a part of unconventional computing, P-systems are proven to be effective in solving complex problems.A software technique is presented here that obtain good results when dealing with such problems. The rules application phase is studied and updated accordingly to obtain the desired results. Certain rules are candidate to be eliminated which can make the model improving in terms of time.     

Color local complexity estimation based steganographic (CLCES) method

In this paper we present the color local complexity estimation based steganographic (CLCES) method that is able of both preventing visual degradation and providing a large embedding capacity. A preprocessing stage is applied in the proposed scheme to improve the steganography security. The embedding capacity of each pixel is determined by the local complexity of the cover image, allowing good visual quality as well as embedding a large amount of secret messages. We classify the pixels using a threshold based on the standard deviation of the local complexity in the cover image to provide a compromise between the embedding capacity and the image visual quality. The experimental results demonstrated that the algorithm CLCES proposed produces insignificant visual distortion due to the hidden message. It provides a high embedding capacity that is superior respect to the offered by the existing schemes. The proposed method is a secure steganographic algorithm; it can resist the image quality measures (IQM) steganalysis attack. The RGB, YCbCr, and HSV color spaces are incorporated in the proposed scheme to ensure that the difference between the cover image and the stego-image which is indistinguishable by the human visual system (HVS). Finally, the proposed scheme is simple, efficient, and feasible for the adaptive steganographic applications.