| Title |
A new multiple robot path planning algorithm: dynamic distributed particle swarm optimization
|
|---|---|
| Published in |
Robotics and Biomimetics, November 2017
|
| DOI | 10.1186/s40638-017-0062-6 |
| Pubmed ID | |
| Authors |
Asma Ayari, Sadok Bouamama |
| Abstract |
Multiple robot systems have become a major study concern in the field of robotic research. Their control becomes unreliable and even infeasible if the number of robots increases. In this paper, a new dynamic distributed particle swarm optimization (D(2)PSO) algorithm is proposed for trajectory path planning of multiple robots in order to find collision-free optimal path for each robot in the environment. The proposed approach consists in calculating two local optima detectors, LODpBest and LODgBest. Particles which are unable to improve their personal best and global best for predefined number of successive iterations would be replaced with restructured ones. Stagnation and local optima problems would be avoided by adding diversity to the population, without losing the fast convergence characteristic of PSO. Experiments with multiple robots are provided and proved effectiveness of such approach compared with the distributed PSO. |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 23% |
| Student > Bachelor | 5 | 19% |
| Student > Master | 2 | 8% |
| Student > Postgraduate | 2 | 8% |
| Other | 1 | 4% |
| Other | 4 | 15% |
| Unknown | 6 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 11 | 42% |
| Computer Science | 7 | 27% |
| Social Sciences | 1 | 4% |
| Design | 1 | 4% |
| Unknown | 6 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 23 March 2022.
All research outputs
#4,856,217
of 23,393,453 outputs
Outputs from Robotics and Biomimetics
#3
of 39 outputs
Outputs of similar age
#86,389
of 330,235 outputs
Outputs of similar age from Robotics and Biomimetics
#2
of 16 outputs
Altmetric has tracked 23,393,453 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 39 research outputs from this source. They receive a mean Attention Score of 1.8. This one scored the same or higher as 36 of them.
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 330,235 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.