ABSTRACT
Simultaneous location and mapping (SLAM) technology is key in robot autonomous navigation. Most visual SLAM (VSLAM) algorithms for dynamic environments cannot achieve sufficient positioning accuracy and real-time performance simultaneously. When the dynamic object proportion is too high, the VSLAM algorithm will collapse. To solve the above problems, this paper proposes an indoor dynamic VSLAM algorithm called YDD-SLAM based on ORB-SLAM3, which introduces the YOLOv5 object detection algorithm and integrates deep information. Firstly, the objects detected by YOLOv5 are divided into eight subcategories according to their motion characteristics and depth values. Secondly, the depth ranges of the dynamic object and potentially dynamic object in the moving state in the scene are calculated. Simultaneously, the depth value of the feature point in the detection box is compared with that of the feature point in the detection box to determine whether the point is a dynamic feature point; if it is, the dynamic feature point is eliminated. Further, multiple feature point optimization strategies were developed for VSLAM in dynamic environments. A public data set and an actual dynamic scenario were used for testing. The accuracy of the proposed algorithm was significantly improved compared to that of ORB-SLAM3. This work provides a theoretical foundation for the practical application of a dynamic VSLAM algorithm.
ABSTRACT
Fiber-coupling surface Plasmon resonance sensor has attractive advantages of information transmission such as small volume, anti-electric magnetic field interference, and online real-time remote detection. In order to improve the performance of the sensor, the effect of the residual fiber thickness and the silver film thickness to the sensitivity of the sensor and the depth of the resonance peaks and full width ar half maximum (FWHM) are analyzed respectively. The results show that the increasing fiber residual thickness weakens the SPR phenomenon, and that the increasing silver film thickness widens the resonance peak, while the sensitivity of the sensor does not change monotonously. Through the integration of refractive index sensing sensitivity and full width at half maximum, figure of merit is presented and regarded as the optimized objective. The optimal design is achieved in the case of the fiber residual thickness for 66. 5 µm, and the silver film thickness for 50 nm. The optimized design with the figure of merit of 98. 67 is expected to be applied in the bio-chemical sensing and analysis.
