Flocking Control of Groups of Mobile Autonomous Agents Via Local Feedback
Long Wang,Hong Shi,Tianguang Chu +2 more
- pp 441-446
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TLDR
A set of coordination control laws are introduced that enable the group of mobile autonomous agents moving in Euclidean space with point mass dynamics to generate the desired stable flocking motion.Abstract:
This paper considers a group of mobile autonomous agents moving in Euclidean space with point mass dynamics. We introduce a set of coordination control laws that enable the group to generate the desired stable flocking motion. The control laws are a combination of attractive/repulsive and alignment forces. By using the control laws, all agent velocities asymptotically approach the desired velocity, collisions can be avoided between agents, and the final tight formation minimizes all agent potentials. Moreover, we prove that the velocity of the center of mass (CoM) either is equal to the desired velocity or exponentially converges to it. Finally, for the case that not all agents know the desired final velocity, we show that the desired flocking motion can still be guaranteedread more
Citations
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Journal ArticleDOI
Virtual leader approach to coordinated control of multiple mobile agents with asymmetric interactions
Hong Shi,Long Wang,Tianguang Chu +2 more
TL;DR: This paper introduces a set of coordination control laws that enable the group of mobile autonomous agents moving in Euclidean space with a virtual leader to generate the desired stable flocking motion, and considers the effect of white noise on the collective dynamics of the group.
Proceedings ArticleDOI
Virtual Leader Approach to Coordinated Control of Multiple Mobile Agents with Asymmetric Interactions
Hong Shi,Long Wang,Tianguang Chu +2 more
TL;DR: In this article, a set of coordination control laws that enable the group to generate the desired stable flocking motion is introduced. But the control laws are a combination of attractive/repulsive and alignment forces, and the control law acting on each agent relies on the state information of its flockmates and the external reference signal.
Journal ArticleDOI
Flocking of multi-agent dynamical systems with intermittent nonlinear velocity measurements
TL;DR: In this article, a new flocking algorithm is proposed to guarantee the states of the velocity variables of all the dynamical agents to converge to consensus while ensuring collision avoidance of the whole group, where each agent is assumed to obtain some nonlinear measurements of the relative velocity between itself and its neighbors only on a sequence of non-overlapping time intervals.
Journal ArticleDOI
Limited Communication Consensus Control of Leader-Following Multi-UUVs in a Swarm System Under Multi-Independent Switching Topologies and Time Delay
TL;DR: Two suitable Lyapunov-Krasovskii functionals will be given to obtaining sufficient consensus conditions and multiple randomly varying leader-follower consensus stability criteria for the Markovian switching swarm system, and it will be proved that the swarm system is stochastically stable.
Journal ArticleDOI
Dynamic formation control for autonomous underwater vehicles
TL;DR: Results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness, even with a concave obstacle, and it has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.
References
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Journal ArticleDOI
Swarming behavior of multi-agent systems
Hong Shi,Long Wang,Tianguang Chu +2 more
TL;DR: The model in this paper is more general than isotropic swarms and the results provide further insight into the effect of the interaction pattern on individual motion in a swarm system.
Journal ArticleDOI
Swarm Dynamics of a Group of Mobile Autonomous Agents
TL;DR: In this article, a simple swarm model is proposed to study collective behavior of a group of mobile autonomous agents interacting through a long range attraction and short range repulsion function, and it is shown that the individuals (agents) will aggregate and eventually form a cohesive cluster of finite size around the swarm centre in a finite time, and the size depends only on the parameters of the swarm model.
Posted Content
Swarming Behavior of Multi-Agent Systems
TL;DR: In this paper, the authors considered a continuous-time anisotropic swarm model with an attraction/repulsion function and showed that the swarm members will aggregate and eventually form a cohesive cluster of finite size around the swarm center.
Posted Content
Aggregation of foraging swarms
TL;DR: The model in this paper is more general than isotropic swarms and its results provide further insight into the effect of the interaction pattern on individual motion in a swarm system.
Book ChapterDOI
Aggregation of foraging swarms
TL;DR: In this article, the authors considered an anisotropic swarm model with an attraction/repulsion function and studied its aggregation properties, showing that the swarm members will aggregate and eventually form a cohesive cluster of finite size around the swarm center.
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