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Autonomous mobile robots (AMRs) play a crucial role in industrial and service fields. The paper aims to build a LiDAR-based simultaneous localization and mapping (SLAM) system used by AMRs to overcome challenges in dynamic and changing environments.

This research introduces SLAM-RAMU, a lifelong SLAM system that addresses these challenges by providing precise and consistent relocalization and autonomous map updating (RAMU). During the mapping process, local odometry is obtained using iterative error state Kalman filtering, while back-end loop detection and global pose graph optimization are used for accurate trajectory correction. In addition, a fast point cloud segmentation module is incorporated to robustly distinguish between floor, walls and roof in the environment. The segmented point clouds are then used to generate a 2.5D grid map, with particular emphasis on floor detection to filter the prior map and eliminate dynamic artifacts. In the positioning process, an initial pose alignment method is designed, which combines 2D branch-and-bound search with 3D iterative closest point registration. This method ensures high accuracy even in scenes with similar characteristics. Subsequently, scan-to-map registration is performed using the segmented point cloud on the prior map. The system also includes a map updating module that takes into account historical point cloud segmentation results. It selectively incorporates or excludes new point cloud data to ensure consistent reflection of the real environment in the map.

The performance of the SLAM-RAMU system was evaluated in real-world environments and compared against state-of-the-art (SOTA) methods. The results demonstrate that SLAM-RAMU achieves higher mapping quality and relocalization accuracy and exhibits robustness against dynamic obstacles and environmental changes.

Compared to other SOTA methods in simulation and real environments, SLAM-RAMU showed higher mapping quality, faster initial aligning speed and higher repeated localization accuracy.

In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.

This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.

This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.

To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.

This paper aims to provide a better understanding of the challenges and potential solutions in Visual Simultaneous Localization and Mapping (SLAM), laying the foundation for its applications in autonomous navigation, intelligent driving and other related domains.

In analyzing the latest research, the review presents representative achievements, including methods to enhance efficiency, robustness and accuracy. Additionally, the review provides insights into the future development direction of Visual SLAM, emphasizing the importance of improving system robustness when dealing with dynamic environments. The research methodology of this review involves a literature review and data set analysis, enabling a comprehensive understanding of the current status and prospects in the field of Visual SLAM.

This review aims to comprehensively evaluate the latest advances and challenges in the field of Visual SLAM. By collecting and analyzing relevant research papers and classic data sets, it reveals the current issues faced by Visual SLAM in complex environments and proposes potential solutions. The review begins by introducing the fundamental principles and application areas of Visual SLAM, followed by an in-depth discussion of the challenges encountered when dealing with dynamic objects and complex environments. To enhance the performance of SLAM algorithms, researchers have made progress by integrating different sensor modalities, improving feature extraction and incorporating deep learning techniques, driving advancements in the field.

To the best of the authors’ knowledge, the originality of this review lies in its in-depth analysis of current research hotspots and predictions for future development, providing valuable references for researchers in this field.

This study aims at the employees’ view on organizational learning (OL). OL is originally assessed in the Strategic Learning Assessment Map (SLAM) at the level of the firm by addressing managers, who rated OL in the SLAM on five dimensions of individual, group, organizational, feed-forward and feedback learning. However, as employees are getting their jobs done discretely and are increasingly making their own decisions, their perspective on OL genuinely matters. Hence, the authors assessed OL at the level of the individual by addressing employees on all levels, who rated OL in a short form of the SLAM (SF-SLAM).

In this paper, the authors focused on the construct validity of this SF-SLAM by investigating its reliability, factorial validity and nomological network. First, they asked whether the SF-SLAM reliably measures OL on five dimensions of individual, group, organizational, feed-forward and feedback learning. Next, they asked whether the SF-SLAM was associated with its nomological network of engaging in innovation-related learning activities, behaving innovatively on the job and showing higher educational levels, intelligence and individual job performances. They used a diverse German employee sample of skilled and unskilled workers and managers (N = 434) and analyzed the data with structural equation modeling.

The SF-SLAM was reliable, but revealed both constrained factorial validity and validity on the basis of its nomological network. First, five dimensions found support in the employee sample, but their correlations were high or very high, except for individual learning. Second, the SF-SLAM showed only few differential relations with variables from its nomological network.

Taken together, the SF-SLAM is short, reliable and only valid for examining individual learning.

This chapter explores the work of a library adult literacy programme working closely with other education providers in Risdon Prison in Australia. The Literacy Service operates as a form of outreach to the prison population who have low literacy levels and are not yet engaged in education or using the prison library. In this context, it is a form of radical inclusion, creating opportunities for those most disadvantaged to access learning. The library services help to create a literate environment for prisoners and provide opportunities for prisoners to increase their engagement in lifelong learning and everyday literacy practices, giving them a better chance of developing their literacy skills. Strategies explored for engaging this cohort include a range of creative projects, small group work and one to one tutoring. The Literacy Service has developed best practice approaches to deliver effective literacy support using strategies and approaches that align with research and these are adapted for work in the prison context. The Literacy Service approach is aligned with the wider prison goals of rehabilitation and reintegration and the chapter explores a theory of change to identify how prison education may be most effective in supporting rehabilitation (Szifris, Fox, & Bradbury, 2018). The library Literacy Service offers safe spaces, opportunities to create social bonds, reshape identity, engage in informal learning and set new goals – key elements found to be critical in rehabilitation. The Prison Library Impact Framework, developed by Finlay and Bates (2018), connects these elements with the theory of change model to propose a tool that may be useful to evaluate prison library services in the future.

Autism spectrum disorders (ASDs) are lifelong developmental disorders that are characterised by abnormalities in reciprocal social interaction and communication and stereotyped behaviours and repetitive interests (ICD‐10: World Health Organization, 1992). Although many people with ASD function without support in the community, outcome studies suggest that rates of employment and independent living are poor. Services often need to provide support in the areas of housing, social, occupational, leisure and emotional function. Additionally, ASDs can be associated with high rates of co‐morbid mental health difficulties including depression, anxiety and obsessive‐compulsive disorders. This paper aims to describe the current situation regarding clinical services and what is required from these services to address co‐morbid mental health needs in adults with an ASD.

The purpose of this paper is to provide a selected bibliography of recent resources on library instruction and information literacy.

The paper introduces and annotates periodical articles, monographs, and audiovisual material examining library instruction and information literacy.

The findings provide information about each source, discusses the characteristics of current scholarship, and describes sources that contain unique scholarly contributions and quality reproductions.

The information may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.

With the college admissions process under the microscope after allegations of bribery, fraud, and other malfeasance, it is even more imperative for public libraries to play a role in helping students reach their fullest potential. From collection development to programming to community partnerships, the public library has a critical role to play in the college admissions process, especially in low-income communities. In a society where many people feel that they are at a disadvantage applying to elite schools already, the public library can offer a path forward and a path of hope.

The purpose of this paper is to provide a selected bibliography of recent resources on library instruction and information literacy.

The paper introduces and annotates periodical articles, monographs, and audiovisual material examining library instruction and information literacy.

Information about each source is provided. The paper discusses the characteristics of current scholarship, and describes sources that contain unique scholarly contributions and quality reproductions.

The information in the paper may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.