The Design of 3D Laser Range Finder for Robot Navigation and Mapping in Industrial Environment with Point Clouds Preprocessing

Olivka, Petr; Mihola, Milan; Novák, Petr; Kot, Tomáš; Babjak, Ján

doi:10.1007/978-3-319-47605-6_30

Cited by 8 publications

(6 citation statements)

References 5 publications

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“…In [ 17 ], a typical approach of combining computer vision, infrared range finders, and dynamic path planning is presented. In the context of industrial automation, [ 11 ] describes the use of 3D laser range finders, inertial measurement units (IMU), and a point cloud technique to dynamically map the environment and perform navigation. In [ 5 ], using laser range finders to detect artificial landmarks for localisation is investigated.…”

Section: Autonomous Robot System Designmentioning

confidence: 99%

“…When combined with SLAM and our motion control algorithm, this enables a robot to manoeuvre towards that target without prior knowledge of the environment or any additional infrastructure deployment. Importantly, the emitter may not be in a fixed position, such as in a factory automation [ 11 ] or indoor delivery [ 12 , 13 , 14 , 15 ] context where targets may be mobile. We use a Pioneer 3-DX mobile robot [ 16 ] as a testbench for our method, with the goal of enabling the Pioneer robot to perform navigation by mapping a cluttered or unknown environment while localising itself relative to a single emitter of non-fixed position.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots

Sherwin

Easte

Chen

et al. 2018

Sensors

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Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system.

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Section: Autonomous Robot System Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots

Sherwin

Easte

Chen

et al. 2018

Sensors

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“…One of the most used methods is Simultaneous Localization and Mapping (SLAM) [2] where the environment is not known, so a vision based system is placed on a robot to observe the area and create a map of it, eventually to perform trajectory planning on top of it. There were many enhancements of the SLAM methods proposed, some of them are compared by Santos [3] and the most common sensors used there are lidars [4][5][6][7] and depth cameras [4,[8][9][10]. However, when the environment is known (indoor areas frequently), the advanced SLAM systems may become redundant and if more robots are deployed, it becomes costly when every single robot has to carry all sensors.…”

Section: Introductionmentioning

confidence: 99%

Smart Building Surveillance System as Shared Sensory System for Localization of AGVs

et al. 2020

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The objective of this study is to extend the possibilities of robot localization in a known environment by using the pre-deployed infrastructure of a smart building. The proposed method demonstrates a concept of a Shared Sensory System for the automated guided vehicles (AGVs), when already existing camera hardware of a building can be utilized for position detection of marked devices. This approach extends surveillance cameras capabilities creating a general sensory system for localization of active (automated) or passive devices in a smart building. The application is presented using both simulations and experiments for a common corridor of a building. The advantages and disadvantages are stated. We analyze the impact of the captured frame’s resolution on the processing speed while also using multiple cameras to improve the accuracy of localization. The proposed methodology in which we use the surveillance cameras in a stand-alone way or in a support role for the AGVs to be localized in the environment has a huge potential utilization in the future smart buildings and cities. The available infrastructure is used to provide additional features for the building control unit, such as awareness of the position of the robots without the need to obtain this data directly from the robots, which would lower the cost of the robots themselves. On the other hand, the information about the location of a robot may be transferred bidirectionally between robots and the building control system to improve the overall safety and reliability of the system.

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“…There are two types of 3-D range finder in industrial applications commonly be used. The first type provides omnidirectional measurements of distance named spinning 2-D range finder [14], The second type only measures the distance based 3D capture hardware system design method in a limited field of view named time of flight (ToF) camera [15]. Assumption 2.1: The obstacle scenarios is static and obstacle's location is known.…”

Section: Introductionmentioning

confidence: 99%

Mobile robot navigation path algorithm in 3d industrial internet of thing (iot) environment based on 5g mobile communication

Ping

Petrenko

2019

Sist. anal.i prikl. inform.

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With the significant growth of the semiconductor industry, creating small devices with powerful processing ability and network capabilities are no longer a dream for engineers. Currently, Internet of Things (IoT) has become one of the hottest topics in both industry and academia of wireless communication field. The idea of the Internet of Things (IoT) is to connect every day physical objects such as microwave, doors, lightings and so on. The technical concept of the IoT is to enables these different physical objects to sense information using sensors and sends this information to a server. Industrial IoT is to integrate various technologies to improve business services in different sectors. It implicitly indicates the behavior of machine-to-machine communications. Each of industrial IoT as service domains has its own communication requirements that are measured differently in both such as reliability, Quality of service (QoS), and privacy. According to the development of industrial automation, the industrial Internet of things (IoT) is widely used in smart factories to capture the data and manage the production. One of the most important components of industrial IoT is the wireless sensor network (WSN), which are easy to deploy and use in indoor industrial environments for a IoT of tasks, such as irrigation, machine condition monitoring, and environment monitoring. There are a IoT of works focusing on the WSN in industrial IoT. For example, in, a WSN-based hidden Markov model is proposed to estimate the occupancy in the building (also see other works [1], [2]). In this paper, the research focus on 3-D mobile robot tracking in 5G wireless communication combine to sensor network and mobile robot path planning. The mobile robot can move fast in the three-dimensional (3-D) indoor industrial environment for many tasks such as the monitoring of possible damages on industrial plants [3], data gathering and transmission from wireless communication [4], transportation [5].

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The Design of 3D Laser Range Finder for Robot Navigation and Mapping in Industrial Environment with Point Clouds Preprocessing

Cited by 8 publications

References 5 publications

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots

Smart Building Surveillance System as Shared Sensory System for Localization of AGVs

Mobile robot navigation path algorithm in 3d industrial internet of thing (iot) environment based on 5g mobile communication

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