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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment
|
|---|---|
| Published in |
Sensors, April 2017
|
| DOI | 10.3390/s17040918 |
| Pubmed ID | |
| Authors |
Branko Ristic, Daniel Angley, Bill Moran, Jennifer L. Palmer |
| Abstract |
Finding the source of an accidental or deliberate release of a toxic substance into the atmosphere is of great importance for national security. The paper presents a search algorithm for turbulent environments which falls into the class of cognitive (infotaxi) algorithms. Bayesian estimation of the source parameter vector is carried out using the Rao-Blackwell dimension-reduction method, while the robots are controlled autonomously to move in a scalable formation. Estimation and control are carried out in a centralised replicated fusion architecture assuming all-to-all communication. The paper presents a comprehensive numerical analysis of the proposed algorithm, including the search-time and displacement statistics. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 38% |
| Researcher | 4 | 14% |
| Student > Doctoral Student | 2 | 7% |
| Student > Bachelor | 2 | 7% |
| Professor | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 7 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 15 | 52% |
| Computer Science | 2 | 7% |
| Medicine and Dentistry | 1 | 3% |
| Physics and Astronomy | 1 | 3% |
| Unknown | 10 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 April 2017.
All research outputs
#20,660,571
of 25,382,440 outputs
Outputs from Sensors
#14,404
of 24,312 outputs
Outputs of similar age
#248,313
of 323,266 outputs
Outputs of similar age from Sensors
#255
of 637 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,312 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 323,266 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 637 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.