scholarly journals Cascades-Based Leader–Follower Formation Tracking and Stabilization of Multiple Nonholonomic Vehicles

2020 ◽  
Vol 65 (8) ◽  
pp. 3639-3646 ◽  
Author(s):  
Mohamed Adlene Maghenem ◽  
Antonio Loria ◽  
Elena Panteley
2018 ◽  
Vol 38 (5) ◽  
pp. 548-557 ◽  
Author(s):  
Guo Yi ◽  
Jianxu Mao ◽  
Yaonan Wang ◽  
Hui Zhang ◽  
Zhiqiang Miao

Purpose The purpose of this paper is to consider the leader-following formation control problem for nonholonomic vehicles based on a novel biologically inspired neurodynamics approach. Design/methodology/approach The interactions among the networked multi-vehicle system is modeled by an undirected graph. First, a distributed estimation law is proposed for each follower vehicle to estimate the state including the position, orientation and linear velocity of the leader. Then, a distributed formation tracking control law is designed based on the estimated state of the leader, where a bio-inspired neural dynamic is introduced to solve the impractical velocity jumps problem. Explicit stability and convergence analyses are presented using Lyapunov tools. Findings The effectiveness and efficiency of the proposed control law are demonstrated by numerical simulations and physical vehicle experiments. Consequently, the proposed protocol can successfully achieve the desired formation under connected topologies while tracking the trajectory generated by the leader. Originality/value This paper proposes a neurodynamics-based leader–follower formation tracking algorithm for multiple nonholonomic vehicles.


2021 ◽  
Vol 111 ◽  
pp. 106549
Author(s):  
Jianhua Wang ◽  
Liang Han ◽  
Xiwang Dong ◽  
Qingdong Li ◽  
Zhang Ren

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4374
Author(s):  
Jose Bernardo Martinez ◽  
Hector M. Becerra ◽  
David Gomez-Gutierrez

In this paper, we addressed the problem of controlling the position of a group of unicycle-type robots to follow in formation a time-varying reference avoiding obstacles when needed. We propose a kinematic control scheme that, unlike existing methods, is able to simultaneously solve the both tasks involved in the problem, effectively combining control laws devoted to achieve formation tracking and obstacle avoidance. The main contributions of the paper are twofold: first, the advantages of the proposed approach are not all integrated in existing schemes, ours is fully distributed since the formulation is based on consensus including the leader as part of the formation, scalable for a large number of robots, generic to define a desired formation, and it does not require a global coordinate system or a map of the environment. Second, to the authors’ knowledge, it is the first time that a distributed formation tracking control is combined with obstacle avoidance to solve both tasks simultaneously using a hierarchical scheme, thus guaranteeing continuous robots velocities in spite of activation/deactivation of the obstacle avoidance task, and stability is proven even in the transition of tasks. The effectiveness of the approach is shown through simulations and experiments with real robots.


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