Search results

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.

To make the robot that have real autonomous ability is always the goal of mobile robot research. For mobile robots, simultaneous localization and mapping (SLAM) research is no longer satisfied with enabling robots to build maps by remote control, more needs will focus on the autonomous exploration of unknown areas, which refer to the low light, complex spatial features and a series of unstructured environment, lick underground special space (dark and multiintersection). This study aims to propose a novel robot structure with mapping and autonomous exploration algorithms. The experiment proves the detection ability of the robot.

A small bio-inspired mobile robot suitable for underground special space (dark and multiintersection) is designed, and the control system is set up based on STM32 and Jetson Nano. The robot is equipped with double laser sensor and Ackerman chassis structure, which can adapt to the practical requirements of exploration in underground special space. Based on the graph optimization SLAM method, an optimization method for map construction is proposed. The Iterative Closest Point (ICP) algorithm is used to match two frames of laser to recalculate the relative pose of the robot, which improves the sensor utilization rate of the robot in underground space and also increase the synchronous positioning accuracy. Moreover, based on boundary cells and rapidly-exploring random tree (RRT) algorithm, a new Bio-RRT method for robot autonomous exploration is proposed in addition.

According to the experimental results, it can be seen that the upgraded SLAM method proposed in this paper achieves better results in map construction. At the same time, the algorithm presents good real-time performance as well as high accuracy and strong maintainability, particularly it can update the map continuously with the passing of time and ensure the positioning accuracy in the process of map updating. The Bio-RRT method fused with the firing excitation mechanism of boundary cells has a more purposeful random tree growth. The number of random tree expansion nodes is less, and the amount of information to be processed is reduced, which leads to the path planning time shorter and the efficiency higher. In addition, the target bias makes the random tree grow directly toward the target point with a certain probability, and the obtained path nodes are basically distributed on or on both sides of the line between the initial point and the target point, which makes the path length shorter and reduces the moving cost of the mobile robot. The final experimental results demonstrate that the proposed upgraded SLAM and Bio-RRT methods can better complete the underground special space exploration task.

Based on the background of robot autonomous exploration in underground special space, a new bio-inspired mobile robot structure with mapping and autonomous exploration algorithm is proposed in this paper. The robot structure is constructed, and the perceptual unit, control unit, driving unit and communication unit are described in detail. The robot can satisfy the practical requirements of exploring the underground dark and multiintersection space. Then, the upgraded graph optimization laser SLAM algorithm and interframe matching optimization method are proposed in this paper. The Bio-RRT independent exploration method is finally proposed, which takes shorter time in equally open space and the search strategy for multiintersection space is more efficient. The experimental results demonstrate that the proposed upgrade SLAM and Bio-RRT methods can better complete the underground space exploration task.

This study aims to introduce the fast reactive tree (FRT*) algorithm for enhancing replanning speed and reducing the overall cost of navigation in unknown dynamic environments.

FRT* comprises four key components: inverted tree build, convex hull construction, dead nodes inform activation and lazy-rewiring replanning. First, an initial path is found from the inverted tree where the valid structure is preserved to minimise re-exploration areas during the replanning phase. As the robot encounters environment changes, convex hulls are extracted to sparsely describe impacted areas. Next, the growth direction of the modified tree is biased by the inform activation of dead nodes to avoid unnecessary exploration. In the replanning phase, the tree structure is optimized using the proposed lazy-rewiring replanning to find a high-quality path with low computation burden.

A series of comprehensive simulation experiments demonstrate that the proposed FRT* algorithm can efficiently replan short-cost feasible paths in unknown dynamic environments. The differential wheeled mobile robot with varying reference linear velocities is used to validate the effectiveness and adaptability of the proposed strategy in real word scenarios. Furthermore, ablation studies are conducted to analyze the significance of the key components of FRT*.

The proposed FRT* algorithm introduces a novel approach to addressing the challenges of navigation in unknown dynamic environments. This capability allows mobile robots to safely and efficiently navigate through unknown and dynamic environments, making the method highly applicable to real-world scenarios.

The review aims to facilitate a broader understanding of platform opening and cooperation and points out potential research directions for scholars.

This study searches Web of Science (WOS) database for relevant literature published between 2010 and 2021 and selects 86 papers for this review. The selected literature is categorized according to three dimensions: the strategic choice of platform opening and cooperation (before opening), the construction of an open platform (during opening) and the impact of platform opening and cooperation (after opening). Through comparative analysis, the authors identify research gaps and propose four future research agendas.

The study finds that the current studies are fragmented, and a research system with a theoretical foundation has not yet formed. In addition, with the development of platform operations, new topics such as platform ecosystems and open platform governance have emerged. In short, there is an urgent need for scholars to conduct exploratory research. To this end, the study proposes four future research agendas: strengthen basic research on platform opening and cooperation, deeply explore the dynamic evolution and cutting-edge models of platform opening and cooperation, analyze potential crises and impacts of platform openness and strengthen research on open platform governance.

This is the first systematic review on platform opening and cooperation. Through categorizing literature into three dimensions, this article clearly shows the research status and provides future research avenues.

The purpose of this study is to explore organizational factors that act as antecedents of open innovation search. The authors aim to empirically examine whether the extent to which the organizational slack is absorbed determines its influence on firms’ openness in innovation search. In addition, the authors also examine the moderating effect of absorptive capacity on the relationship between slack and open innovation search.

This study adopted secondary data from multiple sources (NBER, Compustat and US census) and then constructed a ten-year balanced panel dataset of 298 manufacturers. The generalized least square method was used to explore the determinants of open innovation search among manufacturing firms.

The results of this study reveal that the absorption level of organizational slack indeed determines the openness in innovation search. Specifically, absorbed slack negatively affects a firm’s openness in innovation search, whereas unabsorbed slack promotes open innovation search. Additionally, the relationship between absorbed slack and open innovation search will be less negative with the increase of absorptive capacity.

Different from most previous studies that have examined the performance effect of open search among high-tech and large enterprises, this study focuses on the antecedents of open search strategy in both high- and low-tech, large and small firms. The findings reveal that different forms of organizational slack divergently influence a firm’s open search strategy, contributing to the understanding of the relationship between organizational slack and knowledge search behavior in a broader context, as well as the understanding of the moderating effect of absorptive capacity.

The purpose of this study is to examine the impact of corporate social capital and local embeddedness on perceived business performance of Chinese enterprises operating overseas, whose recent growth resulted from the Belt and Road Initiative.

This study reports the results of a sample of 83 Shaanxi outward foreign direct investment (FDI) firms operating in Africa, Asia, Australia, Europe and North America. In-depth interviews with a few sampled firms are used to develop the survey questionnaire and help interpret the results of statistical analysis.

This study proposes two hypotheses and both are supported by the data. First, corporate social capital is a three-dimensional concept, covering governmental, market and personal sources with each source making an equal, positive effect on perceived overseas performance of the surveyed firms. Second, these firms do better when having developed a higher degree of local embeddedness, a measure on local channels used to obtain information and mobilize resources. While local embeddedness indeed mediates some effect of corporate social capital, both variables have shown direct impact on performance.

Reported findings are from a small sample of 83 firms in an inland Chinese province, and business performance is measured by subjective evaluation rather than economic output.

The practical implication is that a Chinese FDI firm is expected to maintain all three relational channels – governmental, market and interpersonal – because the firm can gain different kinds of information and resources from these sources and each channel is necessary and equally important for the firm’s development. Importantly, it needs a different strategy to maintain and best use each channel. For the Belt and Road Initiative to be effective, China must establish platforms through which enterprises can strengthen and reconfigure their corporate social capital, as well as to cultivate and sustain their local networks in foreign destinations.

This study explores the factors that influence platform-to-platform cooperation (PPC) and designs a theoretical framework for platform research.

This multi-case study includes a combination of exploratory and explanatory case studies.

From the internal factor perspective, channel integration capability, technology-based order matching capability and service innovation capability positively affects the PPC. From the perspective of external factors, the impact of a new platform entry on the PPC depends on market power and complementarities between platforms in the supply and value chains. Diversity of demand also has a positive effect on the PPC, which is moderated by network externalities. It is worth noting that the incumbent platform prefers to diversify its services for collaborating platforms with a higher level of cooperation. In addition, the higher diversity of demand, the stronger the service innovation capability, which indirectly impacts cooperation positively.

The PPC has gained immense popularity in recent years. However, no scholars have investigated the factors influencing the PPC decisions, which warrants further exploration. This study sheds light on the factors and mechanisms that influence the PPC from both internal and external perspectives.

This paper aims to investigate the distributed formation control problem for a multi-quadrotor unmanned aerial vehicle system without linear velocity feedbacks.

A nonlinear controller is proposed based on the orthogonal group SE(3) to obviate singularities and ambiguities of the traditional parameterized attitude representations. A cascade structure is applied in the distributed controller design. The inner loop is responsible for attitude control, and the outer loop is responsible for translational dynamics. To ensure a linear-velocity-free characteristic, some auxiliary variables are introduced to construct virtual signals in distributed controller design. The stability analysis of the proposed distributed control method by the Lyapunov function is provided as well.

A group of four quadrotors with constant reference linear velocity and a group of six quadrotors with varying reference linear velocity are adopted to verify the effectiveness of the proposed strategy.

This is a new innovation for multi-robot formation control method to improve assembly automation.

This study explores the influencing factors on organizational efficiency of the smart logistics ecological chain, and designs the corresponding theoretical framework to guide the practice of enterprises

A multi-case study method is adopted in this study. It includes four companies A, B, C and D in China as the case study objects, collects data through enterprise survey and uses the combination of open coding and spindle coding to process the data. By testing the reliability and validity, the theoretical framework is summarized.

First, organizational efficiency in smart logistics ecological chains is directly related to their service and technology innovation capability. Second, symbiotic relationships, information sharing and customer demand affect the efficiency of smart logistics multi-case ecological chains by influencing their service capacity; their technological innovation capability regulates the mechanism of influence. Third, technological innovation in smart logistics ecological chains positively impacts their service capabilities. Improving technological innovation capability can enhance logistics service capabilities.

According to the characteristics of smart logistics, the theoretical framework about organizational efficiency of smart logistics ecological chain is constructed, which fills the research gap and can provide interesting perspectives for the future research related to the smart logistics ecological chain. At the same time, the findings can also help enterprises to better build the smart logistics ecological chain in practice.

This study explores the influencing factors of smart supply chain innovation (SSCI) for going global companies and designs a theoretical framework.

This paper is a multi-case study that includes a combination of exploratory and explanatory case studies.

First, the authors find that SSCI is embodied in product development and supply chain empowerment, which represent exploitative innovation and explorative innovation, respectively. Meanwhile, supply chain empowerment has a positive impact on product development. Second, the going global policy affects the transformation of supply chain empowerment to SSCI practices. Third, in terms of exploitative innovation, personalized demand positively affects SSCI through product development. Finally, explorative innovation, including emerging technology application and supply chain ecologicalization, has a positive effect on supply chain empowerment and thereby affects SSCI.

Supply chain innovation in the context of a smart economy has gained great popularity. This study sheds light on the influencing factors and mechanisms of SSCI from the exploitative and explorative aspects of innovations.