Formation Transformation Based on Leader-Follower Algorithm

Formation Transformation Based on Leader-Follower Algorithm

Yanyu Duan, Zhiqiang Gao, Zhensheng Peng, Wenshuai Yang, Yun Wang
Copyright: © 2019 |Pages: 19
DOI: 10.4018/IJTHI.2019070103
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

A method based on the leader-follower algorithm is proposed for transformation among the formations. The introduction of the greedy algorithm, behavior-based control and virtual structure help realize the region division and the calculation of the distribution of the leaders and followers in target formation. Collision detection and collision avoidance are proposed to solve path conflicts with error free feedback and effectively maintain the stability of motion. The modeling of transformation is simulated by the shape from a line to a wedged, in which the formation is adjusted by the distance difference obtained by feedback. The experimental results show that it is feasible and effective to implement the formation conversion and formation control, and the system possess a better robustness and stability.
Article Preview
Top

Greedy Algorithm Based On Leader-Follower Method

Combined with greedy algorithm based on the leader-follower algorithm (Giryes, 2016; Singh & Ahmed, 2014), the formation can avoid obstacles and remain the geometric model while moving towards target. Obstacle evading and formation maintaining can be performed simultaneously or in succession. The formation performance could be judged by the performance index (Singh & Ahmed, 2014), which is as shown:

  • 1.

    The path length ratio. It refers to the ratio of the mean to the shortest distance, where the mean equals to the average of all players' paths, and the shortest distance is the equivalent of path between original point and the objective point; the smaller the value, the better.

  • 2.

    Probability of formation retention maintenance. It is the percentage of members in expected positions.

  • 3.

    The time required for operation. It is the time required for the entire team to reach the destination.

Formation Maintenance Based on Leader-Follower Algorithm

The core of leader-follower method (Zhang, Zhang & Liu, 2008) for formation maintenance is that one or some members are appointed as the leader in a formation composed of a plurality of motive objects,, and the rest is as retinues who follow the position and orientation of the leader at a certain range, thereby keeping various formations (Lin, Hwang & Wang, 2014). The structure of group formation is composed of parallel structure and series structure in the control structure of leader-follower algorithm, as below in Figure 1.

Figure 1.

(a) Parallel structure; (b) Series structure

IJTHI.2019070103.f01

Leader is centrally the key of the whole group formations influencing the motion and efficiency, whose information such as status, velocity and direction are shared and visible to the its followers (Morbidi, Mariottini & Prattichizzo, 2010). In series structure, all the followers locate their own positions based on the adjacent leader’s IJTHI.2019070103.m01 controller; in parallel structure, every follower locates its position based on its only leader’s IJTHI.2019070103.m02 controller. Combining the ISS theory and its derivative form LFS theory (Consolini, Morbidi & Prattichizzo, 2008), the stability of the two fundamental formation models is analyzed and compared. The conclusion is drawn that parallel structure with a single leader is more stable than series structure. Because the formation conversion of troops concludes various leaders, parallel structure is adopted in this paper to carry out the formation transformation.

Complete Article List

Search this Journal:
Reset
Volume 20: 1 Issue (2024)
Volume 19: 1 Issue (2023)
Volume 18: 7 Issues (2022): 4 Released, 3 Forthcoming
Volume 17: 4 Issues (2021)
Volume 16: 4 Issues (2020)
Volume 15: 4 Issues (2019)
Volume 14: 4 Issues (2018)
Volume 13: 4 Issues (2017)
Volume 12: 4 Issues (2016)
Volume 11: 4 Issues (2015)
Volume 10: 4 Issues (2014)
Volume 9: 4 Issues (2013)
Volume 8: 4 Issues (2012)
Volume 7: 4 Issues (2011)
Volume 6: 4 Issues (2010)
Volume 5: 4 Issues (2009)
Volume 4: 4 Issues (2008)
Volume 3: 4 Issues (2007)
Volume 2: 4 Issues (2006)
Volume 1: 4 Issues (2005)
View Complete Journal Contents Listing