Path Exploration Research Articles

Topological Map-Based Autonomous Exploration in Large-Scale Scenes for Unmanned Vehicles

Robot autonomous exploration is a challenging and valuable research field that has attracted widespread research interest in recent years. However, existing methods often encounter problems such as incomplete exploration, repeated exploration paths, and low exploration efficiency when facing large-scale scenes. Considering that many indoor and outdoor scenes usually have a prior topological map, such as road navigation maps, satellite road network maps, indoor computer-aided design (CAD) maps, etc., this paper incorporated this information into the autonomous exploration framework and proposed an innovative topological map-based autonomous exploration method for large-scale scenes. The key idea of the proposed method is to plan exploration paths with long-term benefits by tightly merging the information between robot-collected and prior topological maps. The exploration path follows a global exploration strategy but prioritizes exploring scenes outside the prior information, thereby preventing the robot from revisiting explored areas and avoiding the duplication of any effort. Furthermore, to improve the stability of exploration efficiency, the exploration path is further refined by assessing the cost and reward of each candidate viewpoint through a fast method. Simulation experimental results demonstrated that the proposed method outperforms state-of-the-art autonomous exploration methods in efficiency and stability and is more suitable for exploration in large-scale scenes. Real-world experimentation has also proven the effectiveness of our proposed method.

Ecological City Planning and Construction Research

In the process of modern urbanization, the construction of ecological city has become an inevitable trend. With the improvement of economic level, people are increasingly demanding a higher quality of life. Cities are the broadest living space for human beings and the foothold for improving the quality of life. The planning and construction of eco-cities satisfy the harmonious relationship between cities and ecological environment, which is of great significance for the sustainable development of urbanization and conforms to the urbanization requirements of harmonious coexistence between human and nature. There have been a lot of researches on eco-city, mainly involving the path exploration of eco-city construction, the practice situation, and the research related to different factors. At present, the construction of eco-city is in the initial stage of exploration, and still faces some development problems. This paper summarizes the connotation of eco-city, analyzes the problems existing in the current stage of eco-city construction, and puts forward some solutions to these obstacles, aiming at promoting the steady development of eco-city construction.

Exploration of suitable utilization paths for different parts of corn straw based on principal component analysis

Exploration of suitable utilization paths for different parts of corn straw based on principal component analysis

Practical Problems and Path Exploration of Moral Education in Colleges and Universities in the New Era

It is extremely important to do a good job in moral education in the new era, which is of great practical significance to correct the moral deviation of college students, shape a sound personality, strengthen the value guidance of college students and promote the modernization of socialism with Chinese characteristics. Currently, universities have achieved certain results in promoting the work of cultivating virtue. However, due to constraints in areas such as the overall quality of the subjects, innovative carriers, and the educational environment, there are still some issues in terms of recognition, practice, and the subject in the process of cultivating virtue and nurturing talents in universities. To solve these problems, from the perspective of universities, it is necessary to carry out the work of cultivating virtue and nurturing talents comprehensively, involving all personnel, throughout the entire process, and in all aspects. This approach aims to enhance the target and effective nature of ideological and political education in universities, ensuring the implementation of the fundamental task of cultivating virtue and nurturing talents.

A heuristic autonomous exploration method based on environmental information gain during quadrotor flight

Autonomous exploration is a widely studied fundamental application in the field of quadrotor, which requires them to automatically explore unknown space to obtain complete information about the environment. The frontier-based method, one of the representative works on autonomous exploration, drives autonomous determination by the definition of frontier information so that complete information about the environment is available to the quadrotor. However, existing frontier-based methods are able to accomplish the task but still suffer from inefficient exploration, and how to improve the efficiency of autonomous exploration is the focus of research nowadays. Slow frontier generation affecting real-time viewpoint determination and insufficient determination methods affecting the quality of viewpoints are typical of these problems. Therefore, to overcome the aforementioned problems, this article proposes a two-level viewpoint determination method for frontier-based autonomous exploration. First, a sampling-based frontier detection method is presented for faster frontier generation, improving the immediacy of environmental representation compared to traditional traversal-based methods. Second, the access to environmental information during flight is considered for the first time, and an innovative heuristic evaluation function is designed to decide on high-quality viewpoint as the next local navigation target in each exploration iteration. Extensive benchmark and real-world tests are conducted to validate our method. The results confirm that our method optimizes the frontier search time by 85%, the exploration time by around 20%–30%, and the exploration path by 25%–35%.

Analysis and Mechanism Path Exploration On the Professional Ethics and Competence of Teachers in Colleges and Universities

Analysis and Mechanism Path Exploration On the Professional Ethics and Competence of Teachers in Colleges and Universities

Research on the curriculum reform of “Supply Chain Management” under the background of school-enterprise collaborative education

With the rapid development of the logistics industry, the requirements for the training of logistics talents are getting higher and higher. The development of logistics majors in local universities in Xinjiang must also be oriented to Xinjiang’s industries and enterprises, and follow the path of industry-education integration and school-enterprise cooperation. Through the analysis of the current school-enterprise cooperative teaching model, it is found that there are still problems such as the lack of close connection between talent training goals and enterprise production needs, the curriculum is too theoretical, and the construction of the teaching staff needs to be strengthened. In response to the above problems, with the goal of cultivating technical and skilled talents, adhering to the concept of school-enterprise collaborative education, taking the “Supply Chain Management” course as an example, we explore the exploration path of “Supply Chain Management” course reform under the background of school-enterprise collaborative education, in order to Through the method of “introducing enterprises into teaching”, we will improve the quality of Urumqi Vocational University’s supply chain management courses, deepen school-enterprise cooperation, and promote the reform of vocational education teaching.

Design and Implementation of a Career Guidance Program at Gachon University College of Medicine

The ultimate goal of career guidance is to help medical students develop a career plan that matches their personal characteristics, allows them to train in their desired subspecialty, and helps them to adapt well to medical practice after graduation. Gachon Medical School has designed a longitudinal career guidance program called GLORI (Gachon Longitudinal Orientation and Career Development), which is based on the outcome of each phase. The program consists of regular courses and portfolio-based career guidance from a mentor professor. In phase 2 (basic medical science), the “Career Seminar” course was developed. This course focuses on self-understanding through a psychological inventory, exploration of postgraduate career paths, and interviews with professors in specialties of interest. In phase 3 (the integration of basic and clinical science), the “Exploring Nonclinical Career Options” course was introduced. This course presents perspectives from doctors who have followed various pioneering career trajectories, including biomedical engineering, medical journalism, writing, public health, health care administration, the pharmaceutical and medical device industries, and other areas. All teaching methods were designed to encourage student participation. The assessment methods are assignment-based, including self-reflective reports and presentations. In addition, a portfolio-based career guidance program is implemented in phases 3 and 4 (clinical clerkship). It is expected that this case study will serve as a practical example for developing comprehensive career guidance programs for medical schools.

AFL++: A Vulnerability Discovery and Reproduction Framework

Directed greybox fuzzing can mainly be used for vulnerability mining and vulnerability replication. However, there are still some issues with existing directional fuzzing tools. One is that after providing problematic changes or patches, it is not possible to quickly target and discover the problem. Secondly, it is difficult to break through the magic byte path, making it difficult to mine deep vulnerabilities. This article proposes a new vulnerability mining and repair framework: American Fuzz Lop Plus (AFL++). Firstly, we utilize alias analysis to enhance inter-procedural control flow graphs and redefine the distance calculation formula to obtain more accurate distances. Secondly, the Newton interpolation method is used for the energy initialization of each seed to prevent test cases from being filtered out due to low energy. A heuristic energy scheduling algorithm is proposed to judiciously schedule the energy of seeds. During the path exploration phase, by adjusting the seed energy, shorter-distance seeds quickly reach the target; with increasing time, seeds tend to explore deeper paths. We then represent the symbolic distance by the number of instructions passed to reach the target and investigate the shortest path search strategy to achieve path pruning, alleviating the problem of path explosion. Finally, based on the above methods, we implement the AFL++ prototype system, integrating directed greybox fuzzing with symbolic execution technology for vulnerability discovery. By interleaving directed symbolic execution and directed greybox fuzzing, the efficiency of vulnerability discovery and reproduction is effectively enhanced.

Virtual reality technology to enhance the publishing of science and technology journals construction path exploration

The application practice of virtual reality technology in enhanced publishing of sci-tech periodicals is explored by case analysis and comprehensive analysis with the introduction of virtual reality technology as forerunner to promote the innovation of mechanism of sci-tech periodicals. comprehensive analysis with the introduction of virtual reality technology as forerunner to promote the innovation of mechanism of sci-tech periodicals, and the extension of industry chain of Chinese academic periodicals and the upgrading of Chinese academic publications. periodicals, and the extension of industry chain of Chinese academic periodicals and the upgrading of platform intellectualization. The research on The research on the application of virtual reality technology in enhanced publishing of sci-tech journals is still in its infancy at home and abroad, and there are many The research on the application of virtual reality technology in enhanced publishing of sci-tech journals is still in its infancy at home and abroad, and there are many obstacles in the application of virtual reality technology. technology, and proposes that the construction of augmented publishing of scientific journals by virtual re ality technology should be carried out from three aspects: content production, operation and management. three aspects: content production, operation and communication, so as to realize the deep integration of virtual reality technology and scientific journals. The construction of augmented publishing of scientific journals by virtual ality technology should be carried out from three aspects: content production, operation and communication, so as to realize the deep integration of virtual reality technology and scientific journals.

Converting the Intangible Cultural Heritage into the Economical Value in the Perspective of Creative Economic: A Case Study of "Tantou New Year Prints"

Based on the Chinese intangible cultural heritage " Tantou New Year Prints " as the research subject, within the perspective of the "creative economy" in the cultural and creative industries, the basic paths of cultural exploration, focusing on pain points, form translation, and urban regeneration are employed to explore its contemporary value. In the research process, a model is constructed to theoretically innovate and regenerate the "art" of the " Tantou New Year Prints " era. In practice, it hones the "skills" of the era, achieving a mutually reinforcing and winning convergence. Through this exploration, a feasible pathway is established within the perspective of the "creative economy" for the intervention of traditional handicrafts in a corner of the contemporary creative industry network. This provides an effective path and practical validation for the innovation and inheritance of excellent traditional culture in the new era.

Prediction of Mechanical Properties of Cold-Rolled Steel Based on Improved Graph Attention Network

The prediction of mechanical properties of cold-rolled steel is very important for the quality control, process optimization, and cost control of cold-rolled steel, but it is still a challenging task to predict accurately. For the existing graph structure of graph attention networks, it is difficult to effectively establish the complex coupling relationship and nonlinear causal relationship between variables. At the same time, it is considered that the process of cold-rolled steel has typical full-flow process characteristics and the graph attention network makes it difficult to extract the path information between the central node and its higher-order neighborhood. The neural Granger causality algorithm is used to extract the latent relationship between variables, and the basic graph structure of mechanical property prediction data is constructed. Secondly, the node embedding layer is added before the graph attention network, which leverages the symmetry nature of Node2vec method by incorporating both breadth-first and depth-first exploration strategies. This ensures a balanced exploration of diverse paths in the graph, capturing not only local structures but also higher-order relationships. The combined graph attention networks are then able to effectively capture the symmetry path information between nodes and dependencies between variables. The accuracy and superiority of this method are verified by experiments in real cold-rolled steel production cases.

Exploration of Construction Measures and Paths for Urban Parks and Green Spaces Under the Background of Opening and Sharing

Exploration of Construction Measures and Paths for Urban Parks and Green Spaces Under the Background of Opening and Sharing

A dynamic reward-enhanced Q-learning approach for efficient path planning and obstacle avoidance in mobile robotics

PurposeThe purpose of the paper is to propose and demonstrate a novel approach for addressing the challenges of path planning and obstacle avoidance in the context of mobile robots (MR). The specific objectives and purposes outlined in the paper include: introducing a new methodology that combines Q-learning with dynamic reward to improve the efficiency of path planning and obstacle avoidance. Enhancing the navigation of MR through unfamiliar environments by reducing blind exploration and accelerating the convergence to optimal solutions and demonstrating through simulation results that the proposed method, dynamic reward-enhanced Q-learning (DRQL), outperforms existing approaches in terms of achieving convergence to an optimal action strategy more efficiently, requiring less time and improving path exploration with fewer steps and higher average rewards.Design/methodology/approachThe design adopted in this paper to achieve its purposes involves the following key components: (1) Combination of Q-learning and dynamic reward: the paper’s design integrates Q-learning, a popular reinforcement learning technique, with dynamic reward mechanisms. This combination forms the foundation of the approach. Q-learning is used to learn and update the robot’s action-value function, while dynamic rewards are introduced to guide the robot’s actions effectively. (2) Data accumulation during navigation: when a MR navigates through an unfamiliar environment, it accumulates experience data. This data collection is a crucial part of the design, as it enables the robot to learn from its interactions with the environment. (3) Dynamic reward integration: dynamic reward mechanisms are integrated into the Q-learning process. These mechanisms provide feedback to the robot based on its actions, guiding it to make decisions that lead to better outcomes. Dynamic rewards help reduce blind exploration, which can be time-consuming and inefficient and promote faster convergence to optimal solutions. (4) Simulation-based evaluation: to assess the effectiveness of the proposed approach, the design includes a simulation-based evaluation. This evaluation uses simulated environments and scenarios to test the performance of the DRQL method. (5) Performance metrics: the design incorporates performance metrics to measure the success of the approach. These metrics likely include measures of convergence speed, exploration efficiency, the number of steps taken and the average rewards obtained during the robot’s navigation.FindingsThe findings of the paper can be summarized as follows: (1) Efficient path planning and obstacle avoidance: the paper’s proposed approach, DRQL, leads to more efficient path planning and obstacle avoidance for MR. This is achieved through the combination of Q-learning and dynamic reward mechanisms, which guide the robot’s actions effectively. (2) Faster convergence to optimal solutions: DRQL accelerates the convergence of the MR to optimal action strategies. Dynamic rewards help reduce the need for blind exploration, which typically consumes time and this results in a quicker attainment of optimal solutions. (3) Reduced exploration time: the integration of dynamic reward mechanisms significantly reduces the time required for exploration during navigation. This reduction in exploration time contributes to more efficient and quicker path planning. (4) Improved path exploration: the results from the simulations indicate that the DRQL method leads to improved path exploration in unknown environments. The robot takes fewer steps to reach its destination, which is a crucial indicator of efficiency. (5) Higher average rewards: the paper’s findings reveal that MR using DRQL receive higher average rewards during their navigation. This suggests that the proposed approach results in better decision-making and more successful navigation.Originality/valueThe paper’s originality stems from its unique combination of Q-learning and dynamic rewards, its focus on efficiency and speed in MR navigation and its ability to enhance path exploration and average rewards. These original contributions have the potential to advance the field of mobile robotics by addressing critical challenges in path planning and obstacle avoidance.

Theoretical Research and Path Exploration of Chinese Culture Input and Acculturation for Foreign Students from the Perspective of Chinese Character Teaching as a Foreign Language

With the quick development of China, the number of foreign students in China has soared. Teaching Chinese as a second language for foreigners with different backgrounds includes language knowledge, the individual cross-cultural adaptation the Chinese culture spread. Chinese characters is the key point in Chinese language learning for foreign students. The charming of Chinese culture is reflected and transmitted by Chinese characters which can help foreign students understand Chinese culture better. By sorting out the theories on Chinese cultural course and acculturation with the perspective of Chinese characters teaching, exploring the corresponding research paths, this paper proposes a reference for the research on conducting cultural course through the way of teaching Chinese characters for foreign students acculturation.

An Improved Shape Annealing Algorithm for the Generation of Coated Deoxyribonucleic Acid Origami Nanostructures

Abstract In recent years, the field of structural DNA nanotechnology has advanced rapidly due to transformative design tools. Although these tools have been revolutionary, they still bear one overall limitation of requiring users to fully conceptualize their designs before designing. Recently, a simple computational casting technique was developed using generative optimization strategies to automate the DNA origami nanostructure design. This approach employs a shape annealing algorithm, which creates a formal language of honeycomb nanostructures with shape grammars and drives designs from the language toward a desired configuration using simulated annealing. This initial demonstration of the approach can generate novel scaffold routing schemes for creating solid or hollow structures constrained by the boundaries of polyhedral meshes. The results from the initial approach, particularly from the hollow structures, reveal a challenging design space. This simple technique generates novel scaffold routing schemes that do not replicate the overall polyhedral mesh shape and are limited in their ability to control scaffold path exploration in the design space. This paper demonstrates an approach for achieving different levels of consistent effective wall thicknesses and improving the quality of mesh coverage for hollow structures that can be tuned and optimized by introducing a more refined computational casting technique. We achieve these improvements through changes in the simulated annealing algorithm by adding a Hustin move set algorithm that dynamically adjusts the performance of the overall design and redefining how these hollow designs are articulated. This work illustrates how the technique can navigate a challenging design space to generate effective hollow designs.

Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned

This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with the vision to facilitate the novel technologies necessary to reliably explore diverse underground environments despite the grueling challenges they present for robotic autonomy. Due to their geometric complexity, degraded perceptual conditions combined with lack of GNSS support, austere navigation conditions, and denied communications, subterranean settings render autonomous operations particularly demanding. In response to this challenge, we developed the CERBERUS system which exploits the synergy of legged and flying robots, coupled with robust control especially for overcoming perilous terrain, multi-modal and multi-robot perception for localization and mapping in conditions of sensor degradation, and resilient autonomy through unified exploration path planning and local motion planning that reflects robot-specific limitations. Based on its ability to explore diverse underground environments and its high-level command and control by a single human supervisor, CERBERUS demonstrated efficient exploration, reliable detection of objects of interest, and accurate mapping. In this article, we report results from both the preliminary runs and the final Prize Round of the DARPA Subterranean Challenge, and discuss highlights and challenges faced, alongside lessons learned for the benefit of the community.

Practice and Exploration of Chinese Red Opera in University Culture and Art Education

This study takes the practice and exploration of Chinese Red Opera in university culture and art education, and puts forward the corresponding practice methods and exploration paths. Firstly, it introduces the origin and development process of Chinese Red Opera, and analyzes its artistic characteristics and forms of expression. Then the practice and exploration of Chinese Red Opera in university culture and art education. In classroom teaching, teachers can choose red opera works suitable for college students, and design a variety of teaching activities and forms to provide good stage performance opportunities. In the university associations and performances, red opera societies can be established and perform, participate in artistic activities and competitions inside and outside the university, and innovate the performance forms and means of red opera. These practical methods and exploration paths can effectively promote students' learning and understanding of red opera, improve the effect of education, study and explore the innovation and development of red opera in university education, and make contributions to the cultivation of talents with highly cultural and artistic accomplishment.

Exploration and Improvement Path of Local Government Debt Risk Warning Mechanism Based on KMV Model: Taking Bengbu, Anhui as an Example

This article is based on the KMV model and explores methods for improving the local government debt risk warning mechanism under the backdrop of the pandemic, with a case study of Bengbu City in Anhui Province, China. In the context of an economic downturn and the impact of the COVID-19 pandemic, accurately understanding and effectively managing the fiscal risks of local governments is particularly important. The study focuses on analyzing the impact of changes in fiscal revenue and expenditure structures during the pandemic on local debt risks, using the KMV model for in-depth analysis. By comparing fiscal data from different time periods, the effectiveness of the existing local government debt risk warning mechanisms was evaluated. This paper also discusses how to improve risk management and proposes specific strategies and suggestions. These recommendations aim to enhance the efficacy of local government debt warning systems, especially considering the unique challenges brought about by the pandemic and economic changes. The study shows that by improving fiscal risk management and optimizing warning mechanisms, it is possible to better respond to various economic challenges that may arise in the future, providing local governments with more robust and reliable financial risk control plans.

Research on Rural Brand Image Design and the Exploration of Paths under the Strategy of Rural Revitalization

Research on Rural Brand Image Design and the Exploration of Paths under the Strategy of Rural Revitalization