Simulation Experiment and Analysis of GNSS/INS/LEO/5G Integrated Navigation Based on Federated Filtering Algorithm

This article examines the positioning effect of integrated navigation after adding an LEO constellation signal source and a 5G ranging signal source in the context of China’s new infrastructure construction. The tightly coupled Kalman federal filters are used as the algorithm framework. Each signal source required for integrated navigation is simulated in this article. At the same time, by limiting the range of the azimuth angle and visible height angle, different experimental scenes are simulated to verify the contribution of the new signal source to the traditional satellite navigation, and the positioning results are analyzed. Finally, the article compares the distribution of different federal filtering information factors and reveals the method of assigning information factors when combining navigation with sensors with different precision. The experimental results show that the addition of LEO constellation and 5G ranging signals improves the positioning accuracy of the original INS/GNSS by an order of magnitude and ensures a high degree of positioning continuity. Moreover, the experiment shows that the federated filtering algorithm can adapt to the combined navigation mode in different scenarios by combining different precision sensors for navigation positioning.

Polarized light-aided VINS: Global heading measurements and graph optimization based multi-sensor fusion

Polarized skylight is as fundamental a constituent of passive navigation as geomagnetic field. In regards to its applicability to outdoor robot localization, a polarized light-aided VINS (abbreviates ‘visual-inertial navigation system’) modelization dedicated to globally optimized pose estimation and heading correction is constructed. The combined system follows typical visual SLAM (abbreviates ‘simultaneous localization and mapping’) frameworks, and we propose a methodology to fuse global heading measurements with visual and inertial information in a graph optimization based estimator. With ideas of ‘new-added attribute of each vertex and heading error encoded constraint edges’, the heading, as absolute orientation reference, is estimated by Berry polarization model and continuously updated in a graph structure. The formulized graph optimization process for multi-sensor fusion is simultaneously provided. In terms of campus road experiments on Bulldog-CX Robot platform, results are compared against purely stereo camera-dependent and VINS Fusion frameworks, revealing our design is substantially more accurate than others with both locally and globally consistent position and attitude estimates. As essentially passive, anatomically coupled and drifts calibratable navigation mode, the polarized light-aided VINS may therefore be considered as a tool candidate for a class of visual SLAM based multi-sensor fusion.

The Design of Mathematics Teaching Optimization Scheme Based on Data-Driven Decision-Making Technology

In order to improve the effect of classroom teaching and realize the improvement of mathematics teaching quality, this article combines data-driven decision-making technology to design a mathematics teaching plan system and applies data-driven decision-making technology to the design of mathematics teaching plan by improving the big data algorithm. In addition, this paper designs a mathematics teaching plan design system based on data-driven decision-making technology. The system learning module displays the knowledge points in a chapter-sequential navigation mode and stores data or information in the nodes, which are connected to form a network structure through chains. Finally, this paper verifies the designed system with experiments. From the results of the experimental research data, it can be seen that the mathematical teaching plan design system based on the data-driven decision-making technology constructed in this article has good practical effects. On this basis, the system constructed in this article can be verified through further practice.

Optimization method of navigation information mode under the condition of multi-exit city expressway

In recent years, mobile phone navigation software has been widely used, but the voice broadcast information of many navigation software is not clear, which is easy to cause confused driving. Urban expressway is an important artery of the city. The road and traffic conditions of urban expressways are extremely complicated, and there are many types of exits, which can easily cause confused driving. Therefore, optimization of navigation modes under the condition of multi-exit urban expressways is particularly important. Based on the experimental data of simulated driving, this paper focuses on the influence of voice navigation broadcast timing on driving under urban expressway, founding driver’s behavior is significantly different under diverse navigation modes. This paper uses the principal component analysis method to comprehensively evaluate the navigation broadcast timing, and gives the optimal navigation broadcast timings for various multi-exit urban expressways. In most cases, the first broadcast time should be 1500m from the exit. This paper clarifies the impact of navigation broadcast timing on driving, and optimizes the navigation mode of multi-exit urban expressways, which is of great significance for reducing yaw under navigation and improving navigation services.

Mobile Robot Simulation and Navigation in ROS and Gazebo

mobile robots are entering our daily lives as wellas in the industry. Their task is usually associated with carryingout transportation. This leads to the need to performautonomous movement of mobile robots. On the other hand,modern practice is that the planning of most processes is donethrough simulations. Thus, various future production problemscan be anticipated and remedied or improved. The articledescribes the creation of a mobile robot model in the Gazebosimulation environment. Specific settings and features forrunning a mobile robot in autonomous navigation mode underthe robot operating system are presented. The steps for creatinga map, localization and navigation are presented. Experimentshave been conducted to optimize and tune the parameters ofboth the robot model itself and the simulation controlparameters.

Prototype of Robotic Device for Mobility Assistance for the Elderly in Urban Environments

This study aims to develop a prototype of an autonomous robotic device to assist the locomotion of the elderly in urban environments. Among the achievements presented are the control techniques used for autonomous navigation and the software tools and hardware applied in the prototype. This is an extension of a previous work, in which part of the navigation algorithm was developed and validated in a simulated environment. In this extension, the real prototype is controlled by an algorithm based on fuzzy logic to obtain standalone and more-natural navigation for the user of the device. The robotic device is intended to guide an elderly person in an urban environment autonomously, although it also has a manual navigation mode. Therefore, the device should be able to navigate smoothly without sudden manoeuvres and should respect the locomotion time of the user. Furthermore, because of the proposed environment, the device should be able to navigate in an unknown and unstructured environment. The results reveal that this prototype achieves the proposed objective, demonstrating adequate behaviour for navigation in an unknown environment and fundamental safety characteristics to assist the elderly.