Search results

1 – 10 of 492
Article
Publication date: 2 February 2024

Bushi Chen, Xunyu Zhong, Han Xie, Pengfei Peng, Huosheng Hu, Xungao Zhong and Qiang Liu

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 5 October 2023

Zhixiong Chen, Weishan Long, Li Song and Xinglin Li

This paper aims to research the tribological and dynamic characteristics of aeroengine hybrid ceramic bearings through wear experiments and simulation analysis.

Abstract

Purpose

This paper aims to research the tribological and dynamic characteristics of aeroengine hybrid ceramic bearings through wear experiments and simulation analysis.

Design/methodology/approach

First, the authors carried out wear experiments on Si3N4–GCr15 and GCr15–GCr15 friction pairs through the ball-disc wear test rig to explore the tribological properties of their materials. Second, using ANSYS/LS-DYNA simulation software, the dynamic simulation analysis of hybrid bearings was carried out under certain working conditions, and the dynamic contact stress of all-steel bearings of the same size was simulated and compared. Finally, the change of the maximum contact stress of the main bearing under the change of load and rotation speed was studied.

Findings

The results show that the Si3N4–GCr15 pair has better tribological performance. At the same time, under the conditions of high speed and heavy load, the simulation analysis shows that the contact stress between the ceramic ball and the raceway of the ring is smaller than the steel ball. That is, hybrid bearings have better transient mechanical properties than all-steel bearings. With the speed increasing to 12,000 r/min, the maximum stress point will shift in the inner and outer rings.

Originality/value

In this study, the tribological and transient mechanical properties of Si3N4 material were comprehensively analyzed through wear experiments and dynamic simulation analysis, which provided a reference for the design of hybrid bearings for next-generation aeroengines.

Details

Aircraft Engineering and Aerospace Technology, vol. 95 no. 10
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 6 February 2024

Han Wang, Quan Zhang, Zhenquan Fan, Gongcheng Wang, Pengchao Ding and Weidong Wang

To solve the obstacle detection problem in robot autonomous obstacle negotiation, this paper aims to propose an obstacle detection system based on elevation maps for three types…

Abstract

Purpose

To solve the obstacle detection problem in robot autonomous obstacle negotiation, this paper aims to propose an obstacle detection system based on elevation maps for three types of obstacles: positive obstacles, negative obstacles and trench obstacles.

Design/methodology/approach

The system framework includes mapping, ground segmentation, obstacle clustering and obstacle recognition. The positive obstacle detection is realized by calculating its minimum rectangle bounding boxes, which includes convex hull calculation, minimum area rectangle calculation and bounding box generation. The detection of negative obstacles and trench obstacles is implemented on the basis of information absence in the map, including obstacles discovery method and type confirmation method.

Findings

The obstacle detection system has been thoroughly tested in various environments. In the outdoor experiment, with an average speed of 22.2 ms, the system successfully detected obstacles with a 95% success rate, indicating the effectiveness of the detection algorithm. Moreover, the system’s error range for obstacle detection falls between 4% and 6.6%, meeting the necessary requirements for obstacle negotiation in the next stage.

Originality/value

This paper studies how to solve the obstacle detection problem when the robot obstacle negotiation.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 9 February 2024

Ravinder Singh

This paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of…

Abstract

Purpose

This paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of nodes and deploy in free space for reliable trajectory planning.

Design/methodology/approach

Traditional PRM is modified by developing a decision-making strategy for the selection of optimal nodes w.r.t. the complexity of the environment and deploying the optimal number of nodes outside the closed segment. Subsequently, the generated trajectory is made smoother by implementing the modified Bezier curve technique, which selects an optimal number of control points near the sharp turns for the reliable convergence of the trajectory that reduces the sum of the robot’s turning angles.

Findings

The proposed technique is compared with state-of-the-art techniques that show the reduction of computational load by 12.46%, the number of sharp turns by 100%, the number of collisions by 100% and increase the velocity parameter by 19.91%.

Originality/value

The proposed adaptive technique provides a better solution for autonomous navigation of unmanned ground vehicles, transportation, warehouse applications, etc.

Details

Robotic Intelligence and Automation, vol. 44 no. 1
Type: Research Article
ISSN: 2754-6969

Keywords

Article
Publication date: 2 January 2024

Xiangdi Yue, Yihuan Zhang, Jiawei Chen, Junxin Chen, Xuanyi Zhou and Miaolei He

In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 16 January 2024

Nasim Babazadeh, Jochen Teizer, Hans-Joachim Bargstädt and Jürgen Melzner

Construction activities conducted in urban areas are often a source of significant noise disturbances, which cause psychological and health issues for residents as well as…

94

Abstract

Purpose

Construction activities conducted in urban areas are often a source of significant noise disturbances, which cause psychological and health issues for residents as well as long-term auditory impairments for construction workers. The limited effectiveness of passive noise control measures due to the close proximity of the construction site to surrounding neighborhoods often results in complaints and eventually lawsuits. These can then lead to delays and cost overruns for the construction projects.

Design/methodology/approach

The paper proposes a novel approach to integrating construction noise as an additional dimension into scheduling construction works. To achieve this, a building information model, including the three-dimensional construction site layout object geometry, resource allocation and schedule information, is utilized. The developed method explores further project data that are typically available, such as the assigned equipment to a task, its precise location, and the estimated duration of noisy tasks. This results in a noise prediction model by using noise mapping techniques and suggesting less noisy alternative ways of construction. Finally, noise data obtained from sensors in a case study contribute real values for validating the proposed approach, which can be used later to suggest solutions for noise mitigation.

Findings

The results of this study indicate that the proposed approach can accurately predict construction noise given a few available parameters from digital project planning and sensors installed on a construction site. Proactively integrating construction noise control measures into the planning process has benefits for both residents and construction managers, as it reduces construction noise-related disturbances, prevents unexpected legal issues and ensures the health and well-being of the workforce.

Originality/value

While previous research has concentrated on real-time data collection using sensors, a more effective solution would also involve addressing and mitigating construction noise during the pre-construction work planning phase.

Details

Smart and Sustainable Built Environment, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2046-6099

Keywords

Article
Publication date: 21 August 2023

Minghao Wang, Ming Cong, Yu Du, Dong Liu and Xiaojing Tian

The purpose of this study is to solve the problem of an unknown initial position in a multi-robot raster map fusion. The method includes two-dimensional (2D) raster maps and…

Abstract

Purpose

The purpose of this study is to solve the problem of an unknown initial position in a multi-robot raster map fusion. The method includes two-dimensional (2D) raster maps and three-dimensional (3D) point cloud maps.

Design/methodology/approach

A fusion method using multiple algorithms was proposed. For 2D raster maps, this method uses accelerated robust feature detection to extract feature points of multi-raster maps, and then feature points are matched using a two-step algorithm of minimum Euclidean distance and adjacent feature relation. Finally, the random sample consensus algorithm was used for redundant feature fusion. On the basis of 2D raster map fusion, the method of coordinate alignment is used for 3D point cloud map fusion.

Findings

To verify the effectiveness of the algorithm, the segmentation mapping method (2D raster map) and the actual robot mapping method (2D raster map and 3D point cloud map) were used for experimental verification. The experiments demonstrated the stability and reliability of the proposed algorithm.

Originality/value

This algorithm uses a new visual method with coordinate alignment to process the raster map, which can effectively solve the problem of the demand for the initial relative position of robots in traditional methods and be more adaptable to the fusion of 3D maps. In addition, the original data of the map can come from different types of robots, which greatly improves the universality of the algorithm.

Details

Robotic Intelligence and Automation, vol. 43 no. 5
Type: Research Article
ISSN: 2754-6969

Keywords

Article
Publication date: 22 June 2023

Cristiano Busco, Fabrizio Granà and Maria Federica Izzo

Although accounting and reporting visualisations (i.e. graphs, maps and grids) are often used to veil organisations’ untransparent actions, these practices perform irrespectively…

Abstract

Purpose

Although accounting and reporting visualisations (i.e. graphs, maps and grids) are often used to veil organisations’ untransparent actions, these practices perform irrespectively of their ability to represent facts. In this research, the authors explore accounting and reporting visualisations beyond their persuasive and representational purpose.

Design/methodology/approach

By building on previous research on the rhetoric of visualisations, the authors illustrate how the design of accounting visualisations within integrated reports engages managers in a recursive process of knowledge construction, interrogation, reflection and speculation on what sustainable value creation means. The authors articulate the theoretical framework by developing a longitudinal field study in International Fashion Company, a medium-sized company operating in the fashion industry.

Findings

This research shows that accounting and reporting visualisations do not only contribute to creating unclear and often contradicting representations of organisations’ sustainable performance but, at the same time, “open up” and support managers’ unfolding search for “sustainable value” by reducing its unknown meaning into known and understandable categories. The inconsistencies and imperfections that accounting and reporting visualisations leave constitute the conditions of possibility for the interrogation of the unknown to happen in practice, thus augmenting managers’ questioning, reflections and speculation on what sustainable value means.

Originality/value

This study shows that accounting and reporting visualisations can represent good practices (the authors are not saying a “solution”) through which managers can re-appreciate the complexities of measuring and defining something that is intrinsically unknown and unknowable, especially in contexts where best practices have not yet consolidated into a norm. Topics such as climate change and sustainable development are out there and cannot be ignored, cannot be reduced through persuasive accounts and, therefore, need to be embraced.

Details

Accounting, Auditing & Accountability Journal, vol. 37 no. 1
Type: Research Article
ISSN: 0951-3574

Keywords

Article
Publication date: 22 September 2023

Yue Wang, Han Zhao, Haiyue Yang and Xiangshuai Song

The visible time window (VTW) calculation of satellites to ground targets is significant for Earth observation satellites' operation management and control. With the improvement…

Abstract

Purpose

The visible time window (VTW) calculation of satellites to ground targets is significant for Earth observation satellites' operation management and control. With the improvement of satellite maneuvering capability and the complexity of on-orbit observation tasks, the traditional VTW calculation methods can no longer meet the demands of satellite operation management and control due to a large amount of calculation and low efficiency. The purpose of this study is to propose a fast VTW calculation method based on map segmentation named map segmentation method (MSM), to improve the calculation efficiency, and further solve this problem.

Design/methodology/approach

The main feature of the MSM method is to segment the map and subsatellite trajectories and traverse the subsatellite points within a specific range around the target, significantly reducing the search space and the amount of computation and improving computational efficiency.

Findings

Numerical simulations for two satellite orbits are implemented to verify the feasibility of the proposed VTW calculation method, and the traditional traversal method (TM) is also performed for comparative analysis. The results show that the proposed method can obtain the same VTW, using less calculation time than the TM. The computational efficiency is significantly improved, especially for many tasks. The calculation time of observing 500 targets is saved by more than 70%, indicating a broad application prospect.

Originality/value

This paper proposes an original VTW calculation method based on map segmentation to improve the calculation efficiency. The simulation scenarios are designed to verify the accuracy and effectiveness of the proposed method, and the observation targets are randomly distributed on the map. For comparative analysis, the TM is also performed under the same simulation conditions.

Details

Aircraft Engineering and Aerospace Technology, vol. 95 no. 10
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 7 April 2023

Sixing Liu, Yan Chai, Rui Yuan and Hong Miao

Simultaneous localization and map building (SLAM), as a state estimation problem, is a prerequisite for solving the problem of autonomous vehicle motion in unknown environments…

Abstract

Purpose

Simultaneous localization and map building (SLAM), as a state estimation problem, is a prerequisite for solving the problem of autonomous vehicle motion in unknown environments. Existing algorithms are based on laser or visual odometry; however, the lidar sensing range is small, the amount of data features is small, the camera is vulnerable to external conditions and the localization and map building cannot be performed stably and accurately using a single sensor. This paper aims to propose a laser three dimensions tightly coupled map building method that incorporates visual information, and uses laser point cloud information and image information to complement each other to improve the overall performance of the algorithm.

Design/methodology/approach

The visual feature points are first matched at the front end of the method, and the mismatched point pairs are removed using the bidirectional random sample consensus (RANSAC) algorithm. The laser point cloud is then used to obtain its depth information, while the two types of feature points are fed into the pose estimation module for a tightly coupled local bundle adjustment solution using a heuristic simulated annealing algorithm. Finally, the visual bag-of-words model is fused in the laser point cloud information to establish a threshold to construct a loopback framework to further reduce the cumulative drift error of the system over time.

Findings

Experiments on publicly available data sets show that the proposed method in this paper can match its real trajectory well. For various scenes, the map can be constructed by using the complementary laser and vision sensors, with high accuracy and robustness. At the same time, the method is verified in a real environment using an autonomous walking acquisition platform, and the system loaded with the method can run well for a long time and take into account the environmental adaptability of multiple scenes.

Originality/value

A multi-sensor data tight coupling method is proposed to fuse laser and vision information for optimal solution of the positional attitude. A bidirectional RANSAC algorithm is used for the removal of visual mismatched point pairs. Further, oriented fast and rotated brief feature points are used to build a bag-of-words model and construct a real-time loopback framework to reduce error accumulation. According to the experimental validation results, the accuracy and robustness of the single-sensor SLAM algorithm can be improved.

Details

Industrial Robot: the international journal of robotics research and application, vol. 50 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

1 – 10 of 492