This paper presents a discussion on the challenges encountered in localizing mobile robots in large-scale indoor environments, particularly the issues of kidnapping and localization failure, which are prevalent in factories and malls. Visual place recognition (VPR) methods are often used to alleviate these issues; however, in large-scale indoor settings, obtaining ground truth through precise 3D reconstruction using cameras can be time-consuming and challenging due to their limited field of view and varying illumination conditions. LiDAR is more suitable for large-scale mapping due to its wider field of view and its robustness to environmental changes and sensor drifts; however, the cost of LiDAR systems can be prohibitive for indoor applications. RGB-D cameras are lighter and less expensive, making them more suitable for a wide range of applications on multi-robot platforms. Therefore, it is important to investigate the use of RGB-D camera data for place recognition, especially in indoor contexts where only LiDAR maps can be used for place recognition. This paper presents a rigorous comparative study based on existing techniques to identify the key factors in addressing indoor place recognition challenges.
This paper discusses a path-planning algorithm, feasible map algorithm ( FMA), for the classical mover's problem in any dimension using a feasible map representation of a configuration space.
AbstractBackground Obsessive-compulsive disorder (OCD) is a common clinical psychological disease. A large number of studies have shown that OCD patients have cognitive dysfunction, mainly in attention, decision-making, information processing, and so on. Previous studies of OCD information processing focus on processing ways, but studies of its flexibility are limited. As information processing flexibility is a component of executive function and OCD patients have a deficiency in executive function, information processing flexibility could indirectly reflect that OCD patients may be insufficient in information processing flexibility. Hence, we must explore its characteristics in flexible information processing. Methods To eliminate the effects of other comorbid factors, we use the Padua Inventory to screen high obsessive-compulsive tendency (HOC) and low obsessive-compulsive tendency (LOC) individuals as the research object university students. The final sample includes 16 HOC and 15 LOC participants. To make the experiment more in line with ecological validity, the study used a single probability-adjusted Flanker task (i.e., a cue of 20%, 50%, and 80% probability was given before each trial)， combined with an ERP study to investigate information processing flexibility and its corresponding brain mechanisms in individuals with obsessive-compulsive tendencies. Results (1)In the stage of cue presentation, there were no significant differences in P2 (150-250) among individuals with HOC under the three cue probability conditions, but there were significant differences among those with LOC. In the stage of stimulus presentation, there were no significant differences in N2 (100-200) and N3 (250-300) components among individuals with HOC under the three cues, while there were significant differences among those with LOC, and the amplitudes under 80% probability conditions were greater than those under 20% probability conditions; (2)The N2 amplitude of individuals with LOC under effective cues was significantly greater than that under ineffective cues, while there was no significant differences among individuals with HOC. Conclusion Individuals with HOC were less responsive to situational changes and had defects in information processing flexibility, while individuals with LOC were more flexible in information processing, which was manifested in both the cue presentation stage and the stimulus response stage;Individuals with HOC were not easily affected by cues and less strategic in regulating and controlling information processing.
Based on the design equation of mechanism and the least-squares techniques, a rapidly convergent iteration method and simple direct methods for the synthesis of mechanisms are presented. It is proved that the so-called linear superposition method is a special case of the direct methods whose effectiveness depends upon the singular nature of the normal equations of the least-squares method as well as the smallness of the Lagrange multipliers of the compatibility equations for the mechanism. While the significance of the latter has been recognized in the literature, that of the former has not been documented in the literature. By examining the correlation matrix and the condition number for the normal equations, we show that these are near-singular. This property provides a fundamental basis for the direct methods presented in this paper. The sensitivity of solutions to the design specifications and to the precision of floating point computations also is discussed. The theory and associated algorithms can be applied to the synthesis of any planar or spatial mechanism where the use of the least-squares technique is contemplated.
Synthetic aperture radar (SAR) has become one of the most powerful observation tools in the studies of natural environments and Earth resources. However the granular appearance of speckle noise in synthetic aperture radar imagery makes it very difficult to visually and automatically interpret information of SAR data. In this paper, according to the inherent speckle property of SAR image, we proposed a multiscale restoration algorithm by fusing the wavelet coefficients manipulation technique with support vector regression. The kernel parameter was used respectively in the different scale. For preserving sharp edges information, in our algorithm the shrinkage strategy is to compare the estimated value with the original coefficient value of that pixel using the absolute deviation of them. We define a rule for modifying wavelet coefficients based on support vector regression (SVR). Real SAR images are used to evaluate the restoration performance of our proposed algorithm along with another wavelet-based restoration algorithm, as well as the Lee speckle filter. Experimental results show that the proposed method outperforms standard wavelet restoration techniques.
Ground-penetrating radar (GPR) is a well-respected, effective, and efficient geophysical technique. However, for underwater engineering detection and underwater archaeology, the measured B-scan profiles typically contain surface-related multiple waves, which can reduce the signal to noise ratio and interfere with the interpretation of results. SRME is a feedback iteration method based on wave equation, which is frequently utilized in marine seismic explorations but very rarely in GPR underwater engineering detection. To fill this gap, we applied SRME to suppress multiples that appear in GPR underwater images. When we compared the effectiveness of the underwater horizontal layered model and the underwater undulating interface model, we found a high match rate between the predicted and the real-world multiples. In addition, the addition of the Gaussian random noise level with a 4% maximum amplitude to the B-scan profile of the horizontal stratified model yielded satisfactory multiple suppression results. Finally, we applied this method to the B-scan GPR section of actual underwater archaeological images to achieve multiple suppression, which can more effectively weaken and inhibit the surface-related multiples. Both numerical simulations and actual field data show that the SRME method is highly suitable for interpreting waterborne GPR data, and more accurate interpretation can be obtained from the GPR profile after multiples suppression.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Measurement of blood flow velocity is key to understanding physiology and pathology in vivo. While most measurements are performed at the middle of the blood vessel, little research has been done on characterizing the instantaneous blood flow velocity distribution. This is mainly due to the lack of measurement technology with high spatial and temporal resolution. Here, we tackle this problem with our recently developed dual-wavelength line-scan third-harmonic generation (THG) imaging technology. Simultaneous acquisition of dual-wavelength THG line-scanning signals enables measurement of blood flow velocities at two radially symmetric positions in both venules and arterioles in mouse brain in vivo. Our results clearly show that the instantaneous blood flow velocity is not symmetric under general conditions.
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