A star path following mobile robot

Loong, Wong Yuen; Long, Liew Zhen; Hun, Lim Chot

doi:10.1109/icom.2011.5937169

Cited by 27 publications

(12 citation statements)

References 9 publications

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“…The A* star algorithm [31], adapted in [32] tries to find all possible options to reach the destination taking into account the coordinates of the current location and of the destination into the pixels matrix, validates all the paths from the start pixel to the final pixel, thought the walkable paths already set on the first step. After this, it picks up the path that holds the lowest cost [32], which means that is also the shortest path between current location and destination. In the end, the lowest cost path is returned to Map View entity to be painted above the map floor to show the user the path that he/she needs to run on that floor to reach the destination.…”

Section: Find Me! Mobile Appmentioning

confidence: 99%

Beacons and BIM Models for Indoor Guidance and Location

Ferreira

Resende

Martinho

2018

Sensors

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This research work uses a simplified approach to combine location information from a beacon’s propagation signal interaction with a mobile device sensor (accelerometer and gyroscope) with local building information to give real-time location and guidance to a user inside a building. This is an interactive process with visualisation information that can help user’s orientation inside unknown buildings and the data stored from different users can provide useful information about users’ movements inside a public building. Beacons installed on the building at specific pre-defined positions emit signals that give a geographic position with an associated imprecision, related with Bluetooth’s range. This uncertainty is handled by building layout and users’ movement in a developed system that maps users’ position, gives guidance, and stores user movements. This system is based on an App (Find Me!) for Android OS (Operating System) which captures the Bluetooth Low Energy (BLE) signal coming from the beacon(s) and shows, through a map, the location of the user’s smartphone and guide him to the desired destination. Also, the beacons can deliver relevant context information. The application was tested by a panel of new and habitual campus users against traditional wayfinding alternatives yielding navigation times about 30% smaller, respectively.

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Section: Find Me! Mobile Appmentioning

confidence: 99%

Beacons and BIM Models for Indoor Guidance and Location

Ferreira

Resende

Martinho

2018

Sensors

View full text Add to dashboard Cite

show abstract

“…The A* star algorithm [18], adapted in [17] tries to find all possible options to reach the destination taking into account the coordinates of the current location and of the destination into the pixels matrix, validates all the paths from the start pixel to the final pixel, thought the walkable paths already set on the first step. After this, it picks up the path that holds the lowest cost [19], which means that is also the shortest path between current location and destination. In the end, the lowest cost path is returned to Map View entity to be painted above the map floor to show the user the path that he/she needs to run on that floor to reach the destination.…”

Section: Find Me! Mobile Appmentioning

confidence: 99%

Beacons and BIM Models for Indoor Guidance and Location

Ferreira¹,

Resende²,

Martinho³

2018

Preprint

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This research work uses a simplified approach to combine location information from beacons propagation signal interaction with a mobile device with local building information to give real-time location and guidance to a user inside a building. This is an interactive process with visualisation information that can help user's orientation inside unknown buildings and the data stored from different users can provide useful information about users movements inside a public building. Beacons installed on the building at specific pre-defined position emit signals that give a geographic position with an associated imprecision, related with Bluetooth's range. This uncertainty is handled by building layout and users' movement in a developed system that maps users' position, gives guidance and store user movements. This system is based on an App (Find Me!) for Android OS (Operating System) which captures the Bluetooth Low Energy (BLE) signal coming from the beacon(s) and shows, through a map, the location of the user 's smartphone and guide him to the desired destination. Also, the beacons can deliver relevant context information. The application was tested by a panel of new and habitual campus users against traditional wayfinding alternatives yielding navigation times about 30% smaller, respectively.

show abstract

“…Most of these methods have certain advantages in terms of speed, but the path obtained lacks optimization. Some heuristic algorithms, such as A*, D*, are widely used in industry [34][35][36]. Xin et al [37] proposed an improved A* algorithm, which extends the neighborhood propagation of the standard A* algorithm.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm

Chen

Wang

et al. 2019

Sensors

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Mobile robots are becoming more and more widely used in industry and life, so the navigation of robots in dynamic environments has become an urgent problem to be solved. Dynamic path planning has, therefore, received more attention. This paper proposes a real-time dynamic path planning method for mobile robots that can avoid both static and dynamic obstacles. The proposed intelligent optimization method can not only get a better path but also has outstanding advantages in planning time. The algorithm used in the proposed method is a hybrid algorithm based on the beetle antennae search (BAS) algorithm and the artificial potential field (APF) algorithm, termed the BAS-APF method. By establishing a potential field, the convergence speed is accelerated, and the defect that the APF is easily trapped in the local minimum value is also avoided. At the same time, by setting a security scope to make the path closer to the available path in the real environment, the effectiveness and superiority of the proposed method are verified through simulative results.

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A star path following mobile robot

Cited by 27 publications

References 9 publications

Beacons and BIM Models for Indoor Guidance and Location

Beacons and BIM Models for Indoor Guidance and Location

Beacons and BIM Models for Indoor Guidance and Location

Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm

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