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Journal ArticleDOI

Circular motion of multiple nonholonomic robots under switching topology with ordinal ranking

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TLDR
This paper investigates the circular motion of a group of n(n ≥ 2) nonholonomic robots over time-varying communication networks to achieve a balanced circular motion centered at a location determined by each robot under the assumption that the global ranking of any robot is unknown.
Abstract
This paper investigates the circular motion of a group of n(n ≥ 2) nonholonomic robots over time-varying communication networks. We aim to achieve a balanced circular motion centered at a location determined by each robot under the assumption that the global ranking of any robot is unknown. A back-stepping based controller is firstly designed to make all the robots rotate around a common center, the position of which is obtained through executing a consensus algorithm by each robot. Then, the maximum and minimum consensus algorithm and a distributed modified ordinal ranking algorithm are applied to set the rotation radius, angular velocity, and orientation parameters in a distributed manner such that all the robots can uniformly space on the common circle. At last, the effectiveness of the proposed algorithms is illustrated through a simulation example.

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Citations
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Journal ArticleDOI

Distributed multicircular circumnavigation control for UAVs with desired angular spacing

TL;DR: In this paper , a centralized circular enclosing control strategy is derived for multiple UAVs connected by an undirected graph to allow for formation behaviors concerning the moving target, and fixed-time distributed observers are introduced to acquire the state estimates in a fixed time sense, and the upper boundary of settling time can be determined offline irrespective of initial properties.
Journal ArticleDOI

Consensus of discrete-time multi-agent systems over packet dropouts channels

TL;DR: An easy-to-implement linear consensus controller is designed through analyzing the transient properties of the Markov process such that the MASs can reach consensus almost surely for any initial distribution of packet dropouts.
Journal ArticleDOI

Reinforcement learning method for target hunting control of multi‐robot systems with obstacles

TL;DR: In this paper , a target encirclement problem of multi-robot systems is addressed by using reinforcement learning to achieve consensus tracking and virtual circumnavigation points are added to construct the potential energy function.
References
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Proceedings ArticleDOI

Virtual leaders, artificial potentials and coordinated control of groups

TL;DR: In this article, a framework for coordinated and distributed control of multiple autonomous vehicles using artificial potentials and virtual leaders is presented, where virtual leaders can be used to manipulate group geometry and direct the motion of the group.
Journal ArticleDOI

Dynamical aspects of animal grouping: Swarms, schools, flocks, and herds

TL;DR: An attempt is made to describe the motion of grouping individuals kinematically as distinct from simple diffusion or random walk, to model the grouping on the basis of dynamics of animal motion, and to interpret the grouping from the standpoint of advection-diffusion processes.
Journal ArticleDOI

Brief paper: Distributed finite-time attitude containment control for multiple rigid bodies

TL;DR: A distributed sliding-mode estimator and a non-singular sliding surface were given to guarantee that the attitudes and angular velocities of the followers converge, respectively, to the dynamic convex hull formed by those of the leaders in finite time.
Journal ArticleDOI

An Overview of Recent Advances in Event-Triggered Consensus of Multiagent Systems

TL;DR: An overview of recent advances in event-triggered consensus of MASs is provided and some in-depth analysis is made on several event- Triggered schemes, including event-based sampling schemes, model-based event-Triggered scheme, sampled-data-basedevent-trIGgered schemes), and self- triggered sampling schemes.
Book

Cooperative Control of Multi-Agent Systems: Optimal and Adaptive Design Approaches

TL;DR: Optimal cooperative control is introduced and neural adaptive design techniques for multi-agent nonlinear systems with unknown dynamics, which are rarely treated in literature are developed.
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