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Multi-robot laser-based simultaneous localization and mapping (SLAM) in large-scale environments is an essential but challenging issue in mobile robotics, especially in situations wherein no prior knowledge is available between robots. Moreover, the cumulative errors of every individual robot exert a serious negative effect on loop detection and map fusion. To address these problems, this paper aims to propose an efficient approach that combines laser and vision measurements.

A multi-robot visual laser-SLAM is developed to realize robust and efficient SLAM in large-scale environments; both vision and laser loop detections are integrated to detect robust loops. A method based on oriented brief (ORB) feature detection and bag of words (BoW) is developed, to ensure the robustness and computational effectiveness of the multi-robot SLAM system. A robust and efficient graph fusion algorithm is proposed to merge pose graphs from different robots.

The proposed method can detect loops more quickly and accurately than the laser-only SLAM, and it can fuse the submaps of each single robot to promote the efficiency, accuracy and robustness of the system.

Compared with the state of art of multi-robot SLAM approaches, the paper proposed a novel and more sophisticated approach. The vision-based and laser-based loops are integrated to realize a robust loop detection. The ORB features and BoW technologies are further utilized to gain real-time performance. Finally, random sample consensus and least-square methodologies are used to remove the outlier loops among robots.

The purpose of this paper is to describe the trends in residential solid waste collection (RSWC) services in rural China over the past decade and analyze the determinants of these services using nationally representative data.

The authors draw on panel data from three rounds of village-level surveys of 101 villages. The three surveys were conducted in 2005, 2008, and 2012 in five provinces. The authors used fixed-effected regression approach to analyze the determinants of these services.

The results show that in the aftermath of increased investment and policy attention at the national level, the proportion of villages providing RSWC services in rural China increased significantly from 1998 to 2011. However, half of all villages in rural China still did not provide RSWC services as of 2011. Based on econometrics analysis, the authors show that villages that are richer, more populous, and villages with more small hamlets are more likely to provide RSWC services.

The analyses are based on primary survey data and the first to quantify trends in waste management services in the beginning of the twentieth century. The authors believe that the results will have significant policy implications for China in its continuing quest for better waste management policy.

The purpose of this paper is to develop a heuristic method for topology optimization of a continuum with bi-modulus material which is frequently occurred in practical engineering.

The essentials of this model are as follows: First, the original bi-modulus is replaced with two isotropic materials to simplify structural analysis. Second, the stress filed is adopted to calculate the effective strain energy densities (SED) of elements. Third, a floating reference interval of SED is defined and updated by active constraint. Fourth, the elastic modulus of an element is updated according to its principal stresses. Final, the design variables are updated by comparing the local effective SEDs and the current reference interval of SED.

Numerical examples show that the ratio between the tension modulus and the compression modulus of the bi-modulus material in a structure has a significant effect on the final topology design, which is different from that in the same structure with isotropic material. In the optimal structure, it can be found that the material points with the higher modulus are reserved as much as possible. When the ratio is far more than unity, the material can be considered as tension-only material. If the ratio is far less than unity, the material can be considered as compression-only material. As a result, the topology optimization of continuum structures with tension-only or compression-only materials can also be solved by the proposed method.

The value of this paper is twofold: the bi-modulus material layout optimization in a continuum can be solved by the method proposed in this paper, and the layout difference between the structure with bi-modulus material and the same structure but with isotropic material shows that traditional topology optimization result could not be suitable for a real bi-modulus layout design project.

The purpose of this study is to effectively optimize vehicle lane-changing behavior and alleviate traffic congestion in ramp area through the study of vehicle lane-changing behaviors in upstream segment of ramp areas.

In the upstream segment of ramp areas under a connected vehicle environment, different strategies of vehicle group lane-changing behaviors are modeled to obtain the best group lane-changing strategy. The traffic capacity of roads can be improved by controlling group lane-changing behavior and continuously optimizing lane-changing strategy through connected vehicle technologies. This paper constructs vehicle group lane-changing strategies in upstream segment of ramp areas under a connected vehicle environment. The proposed strategies are simulated by VISSIM.

The results show that different lane-changing strategies are modeled through vehicle group in the upstream segment of ramp areas, which can greatly reduce the delay of ramp areas.

The simulation results verify the validity and rationality of the corresponding vehicle group lane-changing behavior model strategies, effectively standardize the driver's lane-changing behavior, and improve road safety and capacity.

The purpose of this paper is to analyze the different types of domestic waste disposal in rural China and the major factors that affect rural household waste disposal behavior.

Stratified and randomly sampled household data are used to describe the disposal of domestic waste in rural China, including domestic garbage and organic waste (human excreta, livestock waste, and kitchen waste); econometric models are estimated to quantify the major determinants of household domestic garbage and human excreta disposal.

While about 30 percent of the domestic garbage in 2008 was discharged to appropriately designated places, more than 40 percent of the garbage was discharged casually. Organic waste at the time of data gathering was still largely used in agricultural production, although a falling trend has been evidenced in recent years. Based on econometric analysis, it becomes clear that income growth, rising population density, and transportation improvements have significantly improved domestic garbage disposal, but negatively affected the recycling of human excreta. The provision of an adequate garbage collection service has the most positive effects on garbage management.

The analyses are based on primary survey data. The results will have significant policy implications on the management of rural domestic waste to maintain better rural environment.

Green building (GB) has been actively promoted in many countries, but it has not become the mainstream in Chinese construction industry due to various reasons. This paper aims to investigate the major driving factors for the development of GB with reference of the Chinese construction market. Twenty-one factors influencing the development of GB were identified through a literature review, questionnaire survey, and face-to-face interview with professionals in the construction industry. Structural equation model was established to identify the critical driving path and three critical factors hierarchies. The result of model analysis also verifies the theoretical hypotheses that government body is the biggest motivation for the development of GB, and the path coefficient is high. The results demonstrate the necessity for the formulation of incentive policies and power of GB propaganda. We identify distinct government and market effects and then induce a government-led GB development path. These findings provide a valuable reference for government body aiming at promoting GB in the construction industry to put forward relevant policies and incentives and for the market body to understand the major driving factors and path when making decisions.

To address the issues of low localization and mapping accuracy, as well as map ghosting and drift, in indoor degraded environments using light detection and ranging-simultaneous localization and mapping (LiDAR SLAM), a real-time localization and mapping system integrating filtering and graph optimization theory is proposed. By incorporating filtering algorithms, the system effectively reduces localization errors and environmental noise. In addition, leveraging graph optimization theory, it optimizes the poses and positions throughout the SLAM process, further enhancing map accuracy and consistency. The purpose of this study resolves common problems such as map ghosting and drift, thereby achieving more precise real-time localization and mapping results.

The system consists of three main components: point cloud data preprocessing, tightly coupled inertial odometry based on filtering and backend pose graph optimization. First, point cloud data preprocessing uses the random sample consensus algorithm to segment the ground and extract ground model parameters, which are then used to construct ground constraint factors in backend optimization. Second, the frontend tightly coupled inertial odometry uses iterative error-state Kalman filtering, where the LiDAR odometry serves as observations and the inertial measurement unit preintegration results as predictions. By constructing a joint function, filtering fusion yields a more accurate LiDAR-inertial odometry. Finally, the backend incorporates graph optimization theory, introducing loop closure factors, ground constraint factors and odometry factors from frame-to-frame matching as constraints. This forms a factor graph that optimizes the map’s poses. The loop closure factor uses an improved scan-text-based loop closure detection algorithm for position recognition, reducing the rate of environmental misidentification.

A SLAM system integrating filtering and graph optimization technique has been proposed, demonstrating improvements of 35.3%, 37.6% and 40.8% in localization and mapping accuracy compared to ALOAM, lightweight and ground optimized lidar odometry and mapping and LiDAR inertial odometry via smoothing and mapping, respectively. The system exhibits enhanced robustness in challenging environments.

This study introduces a frontend laser-inertial odometry tightly coupled filtering method and a backend graph optimization method improved by loop closure detection. This approach demonstrates superior robustness in indoor localization and mapping accuracy.

This study aims to disclose the antecedent factors for predicting support for cruise tourism in the Bahamas. It investigated the relationship between residents’ support for cruise tourism and the four indicators that were the positive/negative impact of cruise tourism on the community, perceived conflicts in sharing information and concerns about the COVID-19 pandemic.

Using 278 surveys of local residents near major cruise ports in the Bahamas, this study identified the salient variables in tourism impact and conflict factors. The survey questionnaire was adapted and developed from relevant studies and modified to suit the context of cruise tourism.

The results revealed that residents’ perceived conflict was insignificantly associated with their support for cruise tourism. In contrast, their concerns about COVID-19 and perceptions of the positive and negative cruise tourism impacts were statistically significant in predicting the likelihood of support for tourism.

This study suggests implications for enhancing the long-term growth of the cruise industry, which is vulnerable to environmental threats such as Covid-19.

This study aims to provide a new perspective on the impact of mortality threats on consumer behavior through the lens of brand anthropomorphism. It examines the mediating effects of control and connectedness motives and the moderating effects of brand roles on the relationship between mediators and brand attitudes.

A preliminary study explored the relationship between pandemic-induced mortality threats and attitudes toward anthropomorphized brands. Study 1 investigated the underlying mechanism, and Study 2 examined the moderating effects of servant or partner roles. Study 3 confirmed the mortality threat effect on anthropomorphic brand attitudes in the absence of the pandemic.

The study revealed that mortality threats enhanced the desire for control and connectedness, which strengthened attitudes toward anthropomorphized brands. The results also indicated matching effects between the motivations for anthropomorphism and brand roles.

This research offers novel insights into the effects of pandemic-induced mortality threats and mortality threats in non-pandemic contexts on anthropomorphic motives. It highlights the influence of these psychological needs on consumer responses to brand roles and provides insights for brand management during a crisis.