An RSSI-based navigation algorithm for a mobile robot in Wireless Sensor Networks

Carvalho, Antonio R.; Ribas, Afonso D.; Neto, Vilar Fiuza da Camara; Nakamura, Eduardo F.; Figueiredo, Carlos M. S.

doi:10.1109/lcn.2012.6423636

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…In another work [202], the approach of the obstacle detection in the RSSI-based sensor network is not discussed. In other works of the RSSI-based target-reaching navigation, some of the works are localization-free navigation, like [170,32,31], and some works requires the odometry of the mobile robot, like [201,30]. In the work [32], the target is localized by the RSSI-based sensor network and a pseudogradient is proposed to navigate the mobile robot to the target.…”

Section: Sensor Network Based Navigation Algorithmsmentioning

confidence: 99%

Sensor Network Based Collision-Free Navigation and Map Building for Mobile Robots

2017

Preprint

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Safe robot navigation is a fundamental research field for autonomous robots including ground mobile robots and flying robots. The primary objective of a safe robot navigation algorithm is to guide an autonomous robot from its initial position to a target or along a desired path with obstacle avoidance. With the development of information technology and sensor technology, the implementations combining robotics with sensor network are focused on in the recent researches. One of the relevant implementations is the sensor network based robot navigation. Moreover, another important navigation problem of robotics is safe area search and map building.In this report, a global collision-free path planning algorithm for ground mobile robots in dynamic environments is presented firstly. Considering the advantages of sensor network, the presented path planning algorithm is developed to a sensor network based navigation algorithm for ground mobile robots. The 2D range finder sensor network is used in the presented method to detect static and dynamic obstacles. The sensor network can guide each ground mobile robot in the detected safe area to the target. The computer simulations and experiments confirm the performance of the presented method. Furthermore, considering the implementations of small-sized flying robots in industry, the presented navigation algorithm is extended into 3D environments. In the presented method, a time-of-flight camera network is used to detect the static and moving obstacles. With the measurements of the sensor network, any flying robot in the workspace is navigated by the presented algorithm from the initial position to the target and avoids any obstacles in the workspace.Moreover, in this report, another navigation problem, safe area search and map building for ground mobile robot, is studied and two algorithms are presented. In the first presented method, we consider a ground mobile robot equipped with a 2D range finder sensor searching a bounded 2D area without any collision and building a complete 2D map of the area. Furthermore, the first presented map building algorithm is extended to another algorithm for 3D map building.

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Section: Sensor Network Based Navigation Algorithmsmentioning

confidence: 99%

Sensor Network Based Collision-Free Navigation and Map Building for Mobile Robots

2017

Preprint

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“…The algorithms described in [2,11,12] are essentially based on an idea to which we refer as direct line approach (see Figure 1 for an illustration). Let m denote the position of the robot and t the position of the target node.…”

Section: Algorithmic Approachesmentioning

confidence: 99%

“…Under ideal model assumptions (i.e., RSSI increases monotonically with decreasing Euclidean distance and the channel is noise-free), p is a point of intersection of the straight line passing through m and y and the orthogonal to this line which passes through t. At position p either a clockwise (cw), or counter-clockwise (ccw) rotation by 90 • , leads to target t. Sun et al [12] as well as Sheu et al [11] consider the case where the mobile node overshoots the ideal point of rotation p due to a certain velocity of the vehicle. Carvalho et al [2] introduced a two-phased approach: As long as the robot is in the "static RSSI range", based on geometric considerations a direction of move is determined that leads into the "meaningful RSSI range" (the area around the target node, where RSSI is above a certain threshold). Within the meaningful RSSI range, the mobile node follows the direct line approach.…”

Section: Algorithmic Approachesmentioning

confidence: 99%

RSSI-based localization of a wireless sensor node with a flying robot

Bohdanowicz

Frey

Funke

et al. 2015

Proceedings of the 30th Annual ACM Symposium on Applied Computing

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We consider the problem of navigating a flying robot to a specific sensor node within a wireless sensor network. This target sensor node periodically sends out beacons. The robot is capable of sensing the received signal strength of each received beacon (RSSI measurements). Existing approaches for solving the sensor spotting problem with RSSI measurements do not deal with noisy channel conditions and/or heavily depend on additional hardware capabilities.In this work we reduce RSSI fluctuations due to noise by continuously sampling RSSI values and maintaining an exponential moving average (EMA). The EMA values enable us to detect significant decrease of the received signal strength. In this case it is reasoned that the robot is moving away from the sensor. We present two basic variants to decide a new moving direction when the robot moves away from the sensor.Our simulations show that our approaches outperform competing algorithms in terms of success rate and flight time. In field experiments with real hardware, a flying robocopter successfully and quickly landed near a sensor placed in an outdoor test environment. Traces show robustness to additional environmental factors not accounted for in our simulations.

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“…In [5], A.R. de Carvalho et al notice the limitation of our previous method and present a further-developed algorithm of RSSI-based navigation.…”

Section: Related Workmentioning

confidence: 99%

RSSI-based mobile robot navigation in grid-pattern wireless sensor network

Zhou

Zhao

Tan

2013

2013 Chinese Automation Congress

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Mobile robot navigation in smart environment has always been one of the most critical issues in robot research. Deployment of wireless sensor network (WSN) in new environment can provide the mobile robot with efficient aid of navigation and tracking. In this paper, we present a feasible scheme of WSN-aided mobile robot navigation which includes initial localization of mobile robot, orientation adjustment, networklayer path planning, motion tracking and correction based on RSSI in Grid-pattern WSN. Unlike other methods of robot navigation which might require a complex and intelligent robotic system for mapping and path planning, the aim of our method is to transfer complex environment detection and calculation from the robot to network and to decrease the reliance of intelligence on the robot itself. Experimental result shows that our proposed scheme is well-performed and can effectively navigate the robot equipped only with simply sensors for communication and obstacle avoidance.

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An RSSI-based navigation algorithm for a mobile robot in Wireless Sensor Networks

Cited by 5 publications

References 11 publications

Sensor Network Based Collision-Free Navigation and Map Building for Mobile Robots

Sensor Network Based Collision-Free Navigation and Map Building for Mobile Robots

RSSI-based localization of a wireless sensor node with a flying robot

RSSI-based mobile robot navigation in grid-pattern wireless sensor network

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