scholarly journals A Study on Various Task-Work Allocation Algorithms in Swarm Robotics

2020 ◽  
Vol 2 (2) ◽  
pp. 123-134
Author(s):  
Annamalai .L ◽  
Mohammed Siddiq. M ◽  
Ravi Shankar. S ◽  
Vigneshwar .S
Keyword(s):  
Mobile Robots ◽  
Swarm Intelligence ◽  
Task Allocation ◽  
Swarm Robotics ◽  
Entire System ◽  
Complex Tasks ◽  
Work Allocation ◽  
Allocation Algorithms

This paper discusses the various task allocation algorithms that have been researched, analyzed, and used in swarm robotics. The main reason for switching over to swarm robotics from ordinary mobile robots is because of its ability to perform complex tasks co-operatively with other bots rather than individually. Furthermore, they can be scaled to perform any kind of tasks. To carry out tasks like foraging, surveying and other such tasks that require swarm intelligence, task allocation plays an important role. It is the crux of the entire system and plays a huge role in the success of the implementation of swarm robotics. Few algorithms that address this task allocation have been briefly discussed here.

scholarly journals Constructing a cohesive pattern for collective navigation based on a swarm of robotics

2021 ◽  
Vol 7 ◽  
pp. e626
Author(s):  
Yehia A. Soliman ◽  
Sarah N. Abdulkader ◽  
Taha M. Mohamed
Keyword(s):  
Mobile Robots ◽  
Execution Time ◽  
Swarm Robotics ◽  
Local Information ◽  
Recruitment Strategy ◽  
Central Control ◽  
Complex Tasks ◽  
Information Interaction ◽  
Collective Navigation ◽  
Swarm Size

Swarm robotics carries out complex tasks beyond the power of simple individual robots. Limited capabilities of sensing and communication by simple mobile robots have been essential inspirations for aggregation tasks. Aggregation is crucial behavior when performing complex tasks in swarm robotics systems. Many difficulties are facing the aggregation algorithm. These difficulties are as such: this algorithm has to work under the restrictions of no information about positions, no central control, and only local information interaction among robots. This paper proposed a new aggregation algorithm. This algorithm combined with the wave algorithm to achieve collective navigation and the recruitment strategy. In this work, the aggregation algorithm consists of two main phases: the searching phase, and the surrounding phase. The execution time of the proposed algorithm was analyzed. The experimental results showed that the aggregation time in the proposed algorithm was significantly reduced by 41% compared to other algorithms in the literature. Moreover, we analyzed our results using a one-way analysis of variance. Also, our results showed that the increasing swarm size significantly improved the performance of the group.

Capturing the swarm intelligence in truckers: The foundation analysis for future swarm robotics in road freight

2021 ◽  
Vol 62 ◽  
pp. 100845
Author(s):  
Mi Gan ◽  
Qiujun Qian ◽  
Dandan Li ◽  
Yi Ai ◽  
Xiaobo Liu
Keyword(s):  
Swarm Intelligence ◽  
Swarm Robotics ◽  
Road Freight

Task Allocation in Case-Based Recommender Systems

2011 ◽  
pp. 268-279 ◽  
Author(s):  
Fabiana Lorenzi ◽  
Daniela Scherer dos Santos ◽  
Denise de Oliveira ◽  
Ana L.C. Bazzan
Keyword(s):  
Swarm Intelligence ◽  
Recommender Systems ◽  
Recommender System ◽  
Task Allocation ◽  
User Preferences ◽  
Cooperative Agents ◽  
Over Time ◽  
Case Based

Case-based recommender systems can learn about user preferences over time and automatically suggest products that fit these preferences. In this chapter, we present such a system, called CASIS. In CASIS, we combined the use of swarm intelligence in the task allocation among cooperative agents applied to a case-based recommender system to help the user to plan a trip.

Evaluation and Comparison of Task Allocation Algorithms for Mesh Networks

2010 ◽  
Author(s):  
Rafal Kaminski ◽  
Leszek Koszalka ◽  
Iwona Pozniak-Koszalka ◽  
Andrzej Kasprzak
Keyword(s):  
Task Allocation ◽  
Mesh Networks ◽  
Allocation Algorithms
Sign in / Sign up

Export Citation Format

Share Document