Mobile Robot Coordination and navigation with directional antennas in positionless Wireless Sensor Networks

Jiang, Jehn-Ruey; Lai, Yung-Liang; Deng, Fucheng

doi:10.1504/ijahuc.2011.040775

Cited by 24 publications

(23 citation statements)

References 11 publications

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“…The simulations were conducted with 30 different random generations of node locations. As seen, the performance of the introduced mechanism compares favorably with existing mechanisms in [6] (FNF Scheme), [8] (LiRosaRus Scheme), and [11] (Reich Scheme). Although, the Inverse Multiquadric RBF and the Gaussian RBF perform worse than the original P-G algorithm, subsequent testing showed their trajectories to be sensitive to the 'σ' parameter (Table (I)) Higher values of 'σ' produces trajectories similar to the ones without interpolation ( Figure (5)).…”

Section: A Navigation Effectivenessmentioning

confidence: 90%

“…The research in this paper was inspired by the research into WSN-assisted AMR navigation in [3], [4], [6], [8] and [11]. It falls in the position-unaware category; the algorithms are independent of node locations utilizing present network topology, and basing their control strategies on the immediate neighborhood of the nodes only.…”

Section: Related Workmentioning

confidence: 99%

“…The scheme utilizes GPS coordinates for the sensor node locations used to assign the artificial potentials. The related research in [1], [6] and [11] utilizes some form of node-to-node navigation, either based on RSS or simple and probabilistic communication hop-count paths. Chen and Henderson [3] can be seen as early proponents of the smart sensor network philosophy using distributed computation and WSN-AMR coordination.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Target-directed navigation using wireless sensor networks and implicit surface interpolation

Deshpande

Grant

Henderson

2012

2012 IEEE International Conference on Robotics and Automation

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This paper extends the novel research for event localization and target-directed navigation using a deployed wireless sensor network (WSN) [4]. The goal is to have an autonomous mobile robot (AMR) navigate to a target-location by: (i) producing an artificial magnitude distribution within the WSN-covered region, and (ii) having the AMR use the pseudogradient from the interpolated distribution in its neighborhood, as it moves towards the target location. Implicit surfaces are used to interpolate the artificial distribution. This scheme only uses the topology of the WSN and received signal strength (RSS) to estimate an efficient navigation path for the AMR. Here, the AMR does not require global coordinates for the region, as it relies on local, neighborhood information alone to navigate. The performance of the scheme is analyzed with hardware experiments and in simulation, using a variety of node-densities and with increasing levels of noise to ensure robustness.

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Section: A Navigation Effectivenessmentioning

confidence: 90%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Target-directed navigation using wireless sensor networks and implicit surface interpolation

Deshpande

Grant

Henderson

2012

2012 IEEE International Conference on Robotics and Automation

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“…Several algorithms based on historical data as well as geometry methods are presented and compared. Jen-Ruey Jiang et al in [7] uses directional antennas and Tree Assisted Navigation scheme to effectively guide the robot in positionless WSN. However, these methods need either too much calculation or the help of additional devices.…”

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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“…Application domains include area coverage, search-and-rescue, target detection and tracking, cooperative transport, etc. [5], [6], [12]. Through this cooperative interaction, the AMRs can effectively address the three-tier challenge.…”

Section: Introductionmentioning

confidence: 99%

Received signal strength based bearing-only robot navigation in a sensor network field

Deshpande

Grant

Draelos

et al. 2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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This paper presents a low-complexity, novel approach to wireless sensor network (WSN) assisted autonomous mobile robot (AMR) navigation. The goal is to have an AMR navigate to a target location using only the information inherent to WSNs, i.e., topology of the WSN and received signal strength (RSS) information, while executing an efficient navigation path. Here, the AMR has neither the location information for the WSN, nor any sophisticated ranging equipment for prior mapping. Two schemes are proposed utilizing particle filtering based bearing estimation with RSS values obtained from directional antennas. Real-world experiments demonstrate the effectiveness of the proposed schemes. In the basic node-to-node navigation scheme, the bearing-only particle filtering reduces trajectory length by 11.7% (indoors) and 15% (outdoors), when compared to using raw bearing measurements. The advanced scheme further reduces the trajectory length by 22.8% (indoors) and 19.8% (outdoors), as compared to the basic scheme. The mechanisms exploit the low-cost, low-complexity advantages of the WSNs to provide an effective method for map-less and ranging-less navigation.

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Mobile Robot Coordination and navigation with directional antennas in positionless Wireless Sensor Networks

Cited by 24 publications

References 11 publications

Target-directed navigation using wireless sensor networks and implicit surface interpolation

Target-directed navigation using wireless sensor networks and implicit surface interpolation

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

Received signal strength based bearing-only robot navigation in a sensor network field

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