SLAM Based Topological Mapping and Navigation

Xue, Wuyang; Ying, Rendong; Gong, Zheng; Miao, Ruihang; Wen, Fei; Liu, Peilin

doi:10.1109/plans46316.2020.9110190

Cited by 10 publications

(10 citation statements)

References 20 publications

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“…The term "Natural Guided Navigation" refers to a number of technologies and Simultaneous Localization and Mapping (SLAM) navigation is the most significant technological advancement as part of it [51], [52]. It means that an AGV equipped with LiDAR and SLAM navigation able to map its surroundings and determine its location using data from the environment [53].…”

Section: ) Natural Guidedmentioning

confidence: 99%

“…A* To plan an efficient path and obstacle avoidance Success to scheduling and find a shortest path for multi-AGV Xue et al [51] A* To search shortest path Success to demonstrate to build reliable topological map with sparce and noisy map points and trajectories of SLAM Zhang [62] Dijkstra To set predetermined route in server Success to re-planned and find another shortest route for multi-AGV in new environment Teleweck & Chandrasekaran [63] A*…”

Section: Zhao Et Al [25]mentioning

confidence: 99%

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A Survey on Navigation Approaches for Automated Guided Vehicle Robots in Dynamic Surrounding

2023

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Automated Guided Vehicle (AGV) have received a lot of attention in recent years in terms of both hardware and software research. Nowadays, the AGV offer more adaptable and effective industrial and transportation system solutions. An AGV navigation techniques is essential to its operation. The decision to use AGV navigation is not simple, though to be suite to the application and sufficient. This paper survey the navigation approaches applied in AGV in the past five years of published academic research. In doing so, this work responds to three related questions: (1) is the AGV classical navigation techniques still relevant to the current application area; (2) is the heuristic navigation techniques itself able to optimize AGV movement in term of guide and strategy; (3) is the use of Artificial Intelligence (AI) in AGV navigation techniques able to increase system performance. As a result, numerous techniques for the AGV navigation have been developed globally. On the other hand, the most popular navigation approaches are provided below for more research.

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Section: ) Natural Guidedmentioning

confidence: 99%

Section: Zhao Et Al [25]mentioning

confidence: 99%

A Survey on Navigation Approaches for Automated Guided Vehicle Robots in Dynamic Surrounding

2023

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“…An edge formed by two important nodes is a line and this line does not intersect with any object in the space. 17 For indoor localization and navigation of autonomous mobile robot, Cheng et al 18 first built the skeleton of the topological map and then added important places into the skeleton. Yuan et al 19 expressed the positions of machines as nodes and established a topological map of the flexible job shop.…”

Section: Related Workmentioning

confidence: 99%

“…Third, the MCF rule is used and the AGV k with the most conflicts with other AGVs is selected (line 15). Fourth, the ECF rule is adopted, and the position and time with the earliest conflict in R k .conset are added to the constraints (lines [16][17]. Then a new shortest path considering constraints for AGV k is replanned (line 18).…”

Section: Improved Upper Layer Algorithmmentioning

confidence: 99%

A multi-AGV fast path planning method based on improved CBS algorithm in workshops

Zhou

Qin

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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Automatic guided vehicles (AGVs) are an important component of workshop logistics distribution systems. With the continuous increase in human cost, unmanned workshops are becoming increasingly popular, and an increasing number of AGVs are being applied to workshop logistics distribution systems. However, with the increasing number of AGVs in the workshop, planning a path quickly for each AGV is challenging, and the response time of multi-AGV fast path planning cannot meet actual requirements. To solve this problem, a multi-AGV fast path planning method based on an improved conflict-based search (ICBS) algorithm is proposed. First, the path planning problem is analyzed, and the environment expression, task, objective and constraint models are established. Subsequently, a two-layer ICBS algorithm is proposed to achieve fast path planning. At the bottom layer, an improved A* algorithm is adopted, and the selection strategy of the nodes is changed when multiple minimum values are equal. In the upper layer, the conflict number, conflict objective and conflict constraint sets are established. Three priority rules including Most Conflicts First (MCF) rule, Earliest Conflict First (ECF) rule, Single Search for Conflict Point (SSCP) rule are used. And a conflict elimination strategy is proposed. Finally, the superiority of the algorithm-solving is verified based on benchmark and actual workshop maps.

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“…The sub-keyframes and keyframes are matched by scanning and matching. In the world coordinate system, sub-keys and keyframes need to be converted, and then added to the factor graph as a closed-loop factor [27].…”

Section: Point Cloud Map Constructionmentioning

confidence: 99%

Research on Slam and Path Planning Method based on Multi-sensor Fusion in Complex Factory Scene

Zhang

Zhou

Hao

et al. 2023

Preprint

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The scene of large factories is complex, and the requirements for production safety are higher. At present, complex factories mainly use manual operation mode to carry out safety inspection, that is, manual inspection and manual recording mode to inspect factory equipment, which has the disadvantages of high labor intensity, low work efficiency and unstable inspection quality. In recent years, with the development of robot navigation related technologies, it has provided a new idea for solving autonomous navigation in large-scale and complex factory environment with variable obstacles. Therefore, we design a slam and path planning method based on multi-sensor fusion, including the establishment of complex and large-scale factory maps, dynamic obstacle avoidance and local path planning, which can achieve accurate and efficient autonomous positioning and effectively generate smooth and safe paths. The security, smoothness, flexibility and efficiency of this method are verified in various complex simulation scenarios and challenging real world. It is proved that this method can meet the performance requirements of positioning and path planning in large-scale complex industrial scenes, and has a good application prospect.

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SLAM Based Topological Mapping and Navigation

Cited by 10 publications

References 20 publications

A Survey on Navigation Approaches for Automated Guided Vehicle Robots in Dynamic Surrounding

A Survey on Navigation Approaches for Automated Guided Vehicle Robots in Dynamic Surrounding

A multi-AGV fast path planning method based on improved CBS algorithm in workshops

Research on Slam and Path Planning Method based on Multi-sensor Fusion in Complex Factory Scene

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