3D model based map building

Comunicación presentada en el IX Workshop de Agentes Físicos (WAF'2008), Vigo, 11-12 septiembre 2008.

Large scale SLAM with visual features

Comunicación presentada en el X Workshop of Physical Agents, Cáceres, 10-11 septiembre 2009.

3D plane-based egomotion for SLAM on semi-structured environment

Several works deal with 3D data in SLAM problem. Data come from a 3D laser sweeping unit or a stereo camera, both providing a huge amount of data. In this paper, we detail an efficient method to extract planar patches from 3D raw data. Then, we use these patches in an ICP-like method in order to address the SLAM problem. Using ICP with planes is not a trivial task. It needs some adaptation from the original ICP. Some promising results are shown for outdoor environment.

Using GNG to improve 3D feature extraction—Application to 6DoF egomotion

Several recent works deal with 3D data in mobile robotic problems, e.g. mapping or egomotion. Data comes from any kind of sensor such as stereo vision systems, time of flight cameras or 3D lasers, providing a huge amount of unorganized 3D data. In this paper, we describe an efficient method to build complete 3D models from a Growing Neural Gas (GNG). The GNG is applied to the 3D raw data and it reduces both the subjacent error and the number of points, keeping the topology of the 3D data. The GNG output is then used in a 3D feature extraction method. We have performed a deep study in which we quantitatively show that the use of GNG improves the 3D feature extraction method. We also show that our method can be applied to any kind of 3D data. The 3D features obtained are used as input in an Iterative Closest Point (ICP)-like method to compute the 6DoF movement performed by a mobile robot. A comparison with standard ICP is performed, showing that the use of GNG improves the results. Final results of 3D mapping from the egomotion calculated are also shown.

Combining visual features and Growing Neural Gas networks for robotic 3D SLAM

The use of 3D data in mobile robotics provides valuable information about the robot’s environment. Traditionally, stereo cameras have been used as a low-cost 3D sensor. However, the lack of precision and texture for some surfaces suggests that the use of other 3D sensors could be more suitable. In this work, we examine the use of two sensors: an infrared SR4000 and a Kinect camera. We use a combination of 3D data obtained by these cameras, along with features obtained from 2D images acquired from these cameras, using a Growing Neural Gas (GNG) network applied to the 3D data. The goal is to obtain a robust egomotion technique. The GNG network is used to reduce the camera error. To calculate the egomotion, we test two methods for 3D registration. One is based on an iterative closest points algorithm, and the other employs random sample consensus. Finally, a simultaneous localization and mapping method is applied to the complete sequence to reduce the global error. The error from each sensor and the mapping results from the proposed method are examined.

Catalyzed addition of acid chlorides to alkynes by unmodified nano-powder magnetite: synthesis of chlorovinyl ketones, furans, and related cyclopentenone derivatives

Inexpensive and commercially available nano-powder magnetite is an excellent catalyst for the addition of acid chlorides to internal and terminal alkynes, yielding the corresponding chlorovinyl ketones in good yields. The process has been applied to the synthesis of 5-chloro-4-arylcyclopent-2-enones, 3-aryl-1H-cyclopenta[a]naphthalen-1-ones, and (E)-3-alkylidene-2,3-dihydro-1H-cyclopenta[a]naphthalen-1-ones, just by changing the nature of the starting acid chloride or the alkyne. All tested processes elapse with an acceptable or excellent regio- and stereo-selectivity. Moreover, the use of the iridium impregnated on magnetite catalyst permits the integration of the chloroacylation process with a second dehydrochlorination–annulation process to yield, in one-pot, 1-aryl-2,4-dialkylfurans in good yields, independently of the nature of the starting reagents, and including the heteroaromatic ones.

Copper Nanoparticles in Click Chemistry

Conspectus: The challenges of the 21st century demand scientific and technological achievements that must be developed under sustainable and environmentally benign practices. In this vein, click chemistry and green chemistry walk hand in hand on a pathway of rigorous principles that help to safeguard the health of our planet against negligent and uncontrolled production. Copper-catalyzed azide–alkyne cycloaddition (CuAAC), the paradigm of a click reaction, is one of the most reliable and widespread synthetic transformations in organic chemistry, with multidisciplinary applications. Nanocatalysis is a green chemistry tool that can increase the inherent effectiveness of CuAAC because of the enhanced catalytic activity of nanostructured metals and their plausible reutilization capability as heterogeneous catalysts. This Account describes our contribution to click chemistry using unsupported and supported copper nanoparticles (CuNPs) as catalysts prepared by chemical reduction. Cu(0)NPs (3.0 ± 1.5 nm) in tetrahydrofuran were found to catalyze the reaction of terminal alkynes and organic azides in the presence of triethylamine at rates comparable to those achieved under microwave heating (10–30 min in most cases). Unfortunately, the CuNPs underwent dissolution under the reaction conditions and consequently could not be recovered. Compelling experimental evidence on the in situ generation of highly reactive copper(I) chloride and the participation of copper(I) acetylides was provided. The supported CuNPs were found to be more robust and efficient catalyst than the unsupported counterpart in the following terms: (a) the multicomponent variant of CuAAC could be applied; (b) the metal loading could be substantially decreased; (c) reactions could be conducted in neat water; and (d) the catalyst could be recovered easily and reutilized. In particular, the catalyst composed of oxidized CuNPs (Cu2O/CuO, 6.0 ± 2.0 nm) supported on carbon (CuNPs/C) was shown to be highly versatile and very effective in the multicomponent and regioselective synthesis of 1,4-disubstituted 1,2,3-triazoles in water from organic halides as azido precursors; magnetically recoverable CuNPs (3.0 ± 0.8 nm) supported on MagSilica could be alternatively used for the same purpose under similar conditions. Incorporation of an aromatic substituent at the 1-position of the triazole could be accomplished using the same CuNPs/C catalytic system starting from aryldiazonium salts or anilines as azido precursors. CuNPs/C in water also catalyzed the regioselective double-click synthesis of β-hydroxy-1,2,3-triazoles from epoxides. Furthermore, alkenes could be also used as azido precursors through a one-pot CuNPs/C-catalyzed azidosulfenylation–CuAAC sequential protocol, providing β-methylsulfanyl-1,2,3-triazoles in a stereo- and regioselective manner. In all types of reaction studied, CuNPs/C exhibited better behavior than some commercial copper catalysts with regard to the metal loading, reaction time, yield, and recyclability. Therefore, the results of this study also highlight the utility of nanosized copper in click chemistry compared with bulk copper sources.