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When robots contribute to eradicate the COVID-19 spread in a context of containment
- Source :
- Progress in Artificial Intelligence
- Publication Year :
- 2021
- Publisher :
- Springer Berlin Heidelberg, 2021.
-
Abstract
- In the era of autonomous robots, multi-targets search methods inspired researchers to develop adapted algorithms to robot constraints, and with the rising of Swarm Intelligence (SI) approaches, Swarm Robotics (SRs) became a very popular topic. In this paper, the problem of searching for an exponentially increasing number of targets in a complex and unknown environment is addressed. Our main objective is to propose a Robotic target search strategy based on the EHO (Elephants Herding Optimization) algorithm, namely Robotic-EHO (REHO). The main additions were the collision-free path planning strategy, the velocity limitation, and the extension to the multi-target version in discrete environments. The proposed method has been the subject of many experiments, emulating the search of infected individuals by COVID-19 in a context of containment within complex and unknown random environments, as well as in the real case study of USA. The particularity of these environments is their increasing targets' number and the dynamic Containment Rate (CR) that we propose. The experimental results show that REHO reacts much better in high Containment Rate, early start search mission, and where the robots' speed is higher than the virus spread speed.
- Subjects :
- Containment (computer programming)
Swarm robotics
Computer science
business.industry
Swarm intelligence
COVID-19
Computational intelligence
Context (language use)
02 engineering and technology
Containment
Target detection problem
Artificial Intelligence
020204 information systems
Autonomous robots
0202 electrical engineering, electronic engineering, information engineering
Regular Paper
Robot
020201 artificial intelligence & image processing
Motion planning
Herding
Artificial intelligence
business
Subjects
Details
- Language :
- English
- ISSN :
- 21926360 and 21926352
- Database :
- OpenAIRE
- Journal :
- Progress in Artificial Intelligence
- Accession number :
- edsair.doi.dedup.....28e56955c0a10b64fc87b4f9da126bf6