Building semantic grid maps for domestic robot navigation

Qi, Xianyu; Wang, Wei; Mei, Yuan; Wang, Yuliang; Li, Mingbo; Lin, Xue; Sun, Yingpin

doi:10.1177/1729881419900066

Cited by 21 publications

(6 citation statements)

References 36 publications

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“…A directly organized semantic map involves attaching semantic tags to physical elements in the environment. Xianyu Qi et al [44] proposed a semantic grid map that uses low-cost sonar and binocular stereo vision sensors to construct the semantic grid map of the target by correctly fusing the occupation grid map and the target point cloud. The topological space of each object is defined, and the room semantics are obtained through topological segmentation.…”

Section: Semantic Mapsmentioning

confidence: 99%

Map representations for mobile robot localization

Zhang,

2024

Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023)

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Localization is a prerequisite for mobile robots to achieve path planning, autonomous navigation, and decision-making. In localization, maps provide mobile robots with the ability to perceive and model the environment, so the choice of an appropriate map representation has a significant impact on the localization effect of mobile robots. From the perspective of usage matching, this paper divides map representations for mobile robot localization into four categories based on different focuses of describing the environment, which are metric maps, feature maps, topological maps, and semantic maps. The principles, characteristics, and classic cases of these representations are also analyzed in this paper. Furthermore, the applicable working conditions of each type of map representation are summarized to provide effective guidance for mobile robot localization.

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Section: Semantic Mapsmentioning

confidence: 99%

Map representations for mobile robot localization

Zhang,

2024

Fourth International Conference on Mechanical Engineering, Intelligent Manufacturing, and Automation Technology (MEMAT 2023)

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“…To construct an occupancy grid map based on laser SLAM, the key is to use the prior information to calculate the posterior probability of the map, and then identify the grid state, i.e., unknown, idle, or occupied [41,42]. The grid state schemas formed after twodimensional (2D) LiDAR scanning are shown in Figure 8; O g X g Y g and O b X b Y b are the grid coordinate system and body coordinate system, respectively.…”

Section: Construction Of Grid Map and Test 421 Principle Of Laser Mappingmentioning

confidence: 99%

Research on Visual Positioning of a Roadheader and Construction of an Environment Map

et al. 2021

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The autonomous positioning of tunneling equipment is the key to intellectualization and robotization of a tunneling face. In this paper, a method based on simultaneous localization and mapping (SLAM) to estimate the body pose of a roadheader and build a navigation map of a roadway is presented. In terms of pose estimation, an RGB-D camera is used to collect images, and a pose calculation model of a roadheader is established based on random sample consensus (RANSAC) and iterative closest point (ICP); constructing a pose graph optimization model with closed-loop constraints. An iterative equation based on Levenberg–Marquadt is derived-, which can achieve the optimal estimation of the body pose. In terms of mapping, LiDAR is used to experimentally construct the grid map based on open-source algorithms, such as Gmapping, Cartographer, Karto, and Hector. A point cloud map, octree map, and compound map are experimentally constructed based on the open-source library RTAB-MAP. By setting parameters, such as the expansion radius of an obstacle and the updating frequency of the map, a cost map for the navigation of a roadheader is established. Combined with algorithms, such as Dijskra and timed-elastic-band, simulation experiments show that the combination of octree map and cost map can support global path planning and local obstacle avoidance.

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“…The first step of cutting path planning is to model the environment of the cross-section containing gangue and describe the overall environment information as a mathematical model including location information and attribute information. 36 To simplify, the inner concave surface formed by swing cutting can be projected onto the plane composed of roadway height and roadway width, as illustrated in Figure 2(a). Hence, path planning on projection plane is equal to it on concave surface.…”

Section: Grid Map Model and Gangue Generationmentioning

confidence: 99%

Full coverage cutting path planning of robotized roadheader to improve cutting stability of the coal lane cross-section containing gangue

Zhang

Liu

Jia

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part C:

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The purpose of this work is to improve the cutting stability of robotized roadheader through the full coverage cutting path planning of the coal lane cross-section containing gangue. Cutting gangue will bring serious pick wear and severe vibration, which will reduce the service life of robotized roadheader. Therefore, the strategy that avoiding the gangue and cutting the remaining coal-rock was recommended. Firstly, the environment grid map of the cross-section containing gangue was established and the grid attribute was assigned. To describe the arbitrary position of gangue, a random generation method was developed. On this basis, the combination of biologically inspired neural network (BINN) and floating template method was proposed to overcome the shortcomings of traditional BINN and the full coverage cutting path planning simulation was carried out. The simulation shows a better result that the average repetition rate is approximately 10% under the condition that the cutting coverage rate is more than 95%. Finally, the cutting experiment of the coal-rock sample containing gangue on the robotized roadheader cutting platform was performed. Based on the infrared thermography and cutting signal obtained by the previous round cutting, the cutting path of the second round was planned and the cutting experiment was conducted. The experiment results show that the cutting temperature rise and the cutting vibration of the second round cutting can be effectively reduced by approximately 60% and 90%, which demonstrated that the cutting stability of the cross-section containing gangue can be effectively improved by the cutting path planning strategy of avoiding gangue.

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Building semantic grid maps for domestic robot navigation

Cited by 21 publications

References 36 publications

Map representations for mobile robot localization

Map representations for mobile robot localization

Research on Visual Positioning of a Roadheader and Construction of an Environment Map

Full coverage cutting path planning of robotized roadheader to improve cutting stability of the coal lane cross-section containing gangue

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