Pablo Jiménez

3D collision detection: a survey

Abstract Many applications in Computer Graphics require fast and robust 3D collision detection algorithms. These algorithms can be grouped into four approaches: space–time volume intersection, swept volume interference, multiple interference detection and trajectory parameterization. While some approaches are linked to a particular object representation scheme (e.g., space–time volume intersection is particularly suited to a CSG representation), others do not. The multiple interference detection approach has been the most widely used under a variety of sampling strategies, reducing the collision detection problem to multiple calls to static interference tests. In most cases, these tests boil down to detecting intersections between simple geometric entities, such as spheres, boxes aligned with the coordinate axes, or polygons and segments. The computational cost of a collision detection algorithm depends not only on the complexity of the basic interference test used, but also on the number of times this test is applied. Therefore, it is crucial to apply this test only at those instants and places where a collision can truly occur. Several strategies have been developed to this end: (1) to find a lower time bound for the first collision, (2) to reduce the pairs of primitives within objects susceptible of interfering, and (3) to cut down the number of object pairs to be considered for interference. These strategies rely on distance computation algorithms, hierarchical object representations, orientation-based pruning criteria, and space partitioning schemes. This paper tries to provide a comprehensive survey of all these techniques from a unified viewpoint, so that well-known algorithms are presented as particular instances of general approaches.

Carbon Nanotube Effect on Polyaniline Morphology in Water Dispersible Composites

A straightforward, template-free chemical oxidative polymerization of aniline was used to prepare nanofibrillar polyaniline (nf-PANI) and a set of corresponding composites with multiwall carbon nanotubes (MWNTs). All the products showed remarkable water dispersibility since they are formed by hydrophilic particles of nanometric size. A comparative study performed on composites in a wide range of MWNT loadings has led to two main conclusions: on one hand, the presence of MWNTs affects neither the chemical structure nor the crystallinity of polyaniline. On the other hand, even small amounts of MWNTs have a significant effect on the morphology of polyaniline in composites. This effect is noticeable not only in electron microscopy images but also in the UV-vis absorbance of water dispersions and electrical conductivity behavior in the solid state. Competition between nucleation sites during polymerization is proposed as an explanation for these phenomena.

Nanofibrilar Polyaniline: Direct Route to Carbon Nanotube Water Dispersions of High Concentration

Water dispersible nanofibrilar polyaniline (NF-PANI) provides a novel and direct route towards carbon nanotube water dispersions of high concentration. Carrying out the chemical synthesis of NF-PANI in the presence of carbon nanotubes (CNTs) results in an entirely nanostructured nanofibrilar polyaniline/carbon nanotube (NF-PANI/CNT) composite material that contains well segregated CNTs partially coated by NF-PANI. This new approach is simple, fast, and inexpensive, and enables the direct preparation of stable and homogeneous dispersions of the composites in water at concentrations up to 10 mg · mL(-1) , even for the highest CNT loadings of 50 wt.-% without the participation of surfactants or stabilizers.

An efficient algorithm for searching implicit AND/OR graphs with cycles

Abstract We present an efficient AO ∗ -like algorithm that handles cyclic graphs without neither unfolding the cycles nor looping through them. Its top-down search strategy is based on Mahanti and Bagchis CF [J. ACM 32 (1985) 28], whereas its bottom-up revision process is inspired in Chakrabartis REV ∗ [Artificial Intelligence 65 (1994) 329]. However, important modifications have been introduced in both algorithms to attain a true integration and gain efficiency. Proofs of correctness and completeness are included. Up to our knowledge, the resulting algorithm—called CFC REV ∗ —is the most efficient one available for this problem.

Charge transport properties of water dispersible multiwall carbon nanotube-polyaniline composites

The transmission electron microscopy images of in situ prepared multiwall carbon nanotubes (MWNTs) and polyaniline (PANI) composites show that nanotubes are well dispersed in aqueous medium, and the nanofibers of PANI facilitate intertube transport. Although low temperature transport indicates variable range hopping (VRH) mechanism, the dc and ac conductivity become temperature independent as the MWNT content increases. The onset frequency for the increase in conductivity is observed to be strongly dependent on the MWNT weight percent, and the ac conductivity can be scaled onto a master curve. The negative magnetoresistance is attributed to the forward interference scattering mechanism in VRH transport.

Photovoltaic textile structure using polyaniline/carbon nanotube composite materials

In this paper, an investigation of flexible electrodes for photovoltaic textile structures utilizing polymer‐based organic materials is presented. The composite structure consisting of a blend of water dispersible carbon nanotube:polyaniline (CNT:PANI) components with poly(3,4 ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) was applied to be used as the hole collecting electrode in photovoltaic textile applications. Both photovoltaic textiles and conventional solar cells were fabricated by using a blend of poly(3‐hexylthiophene‐2,5‐diyl) (P3HT):(6,6)‐phenyl C61‐butyric acid methyl ester (PCBM). All devices were characterized by measuring current versus voltage characteristics under AM 1.5 conditions. The nanoscale morphology of the photovoltaic structures was investigated using scanning electron microscopy and atomic force microscopy.

Speeding up interference detection between polyhedra

A classical paradigm for interference detection between polyhedra consists in testing all edges of one polyhedron against all faces of the other one for intersection. If the relative orientation of the polyhedra is fixed, only certain edge-face pairs can intersect first, when the polyhedra come into contact. These candidate pairs are efficiently determined using a representation which the authors call spherical face orientation graph. By applying the interference test to candidates only, the computational effort is significantly reduced, as shown by experimental results with convex polyhedra. In the non-convex case, the strategy is conservative, but it still leads to savings.

Benefits of applicability constraints in decomposition-free interference detection between nonconvex polyhedral models

Nonconvex polyhedral models of workpieces or robot parts can be directly tested for interference, without resorting to a previous decomposition into convex entities. We show that this interference detection, based on the elemental edge face intersection test, can be performed efficiently: a strategy based on applicability constraints reduces drastically the set of edge - face pairings that have to be considered for intersection. This is accomplished by using an appropriate representation, the spherical face orientation graph, developed by the authors, as well as feature pairing algorithms based on the plane sweep paradigm that have been adapted to work on that representation. Furthermore, the benefits of such a strategy extend to the computation of a lower distance bound between the polyhedra, both lowering the computational effort and improving the quality of the bound. Experimental results confirm the expected advantages of this strategy.

Visually-guided robot navigation: From artificial to natural landmarks

Landmark-based navigation in unknown unstructured environments is far from solved. The bottleneck nowadays seems to be the fast detection of reliable visual references in the image stream as the robot moves. In our research, we have decoupled the navigation issues from this visual bottleneck, by first using artificial landmarks that could be easily detected and identified. Once we had a navigation system working, we developed a strategy to detect and track salient regions along image streams by just performing on-line pixel sampling. This strategy continuously updates the mean and covariances of the salient regions, as well as creates, deletes and merges regions according to the sample flow. Regions detected as salient can be considered as potential landmarks to be used in the navigation task.

Learning Force-Based Robot Skills from Haptic Demonstration

Locally weighted as well as Gaussian mixtures learning algorithms are suitable strategies for trajectory learning and skill acquisition, in the context of programming by demonstration. Input streams other than visual information, as used in most applications up to date, reveal themselves as quite useful in trajectory learning experiments where visual sources are not available. For the first time, force/torque feedback through a haptic device has been used for teaching a teleoperated robot to empty a rigid container. The memory-based LWPLS and the non-memory-based LWPR algorithms [1,2,3], as well as both the batch and the incremental versions of GMM/GMR [4,5] were implemented, their comparison leading to very similar results, with the same pattern as regards to both the involved robot joints and the different initial experimental conditions. Tests where the teacher was instructed to follow a strategy compared to others where he was not lead to useful conclusions that permit devising the new research stages, where the taught motion will be refined by autonomous robot rehearsal through reinforcement learning.