20 research outputs found
Multi-objective Compositions for Collision-Free Connectivity Maintenance in Teams of Mobile Robots
Compositional barrier functions are proposed in this paper to systematically
compose multiple objectives for teams of mobile robots. The objectives are
first encoded as barrier functions, and then composed using AND and OR logical
operators. The advantage of this approach is that compositional barrier
functions can provably guarantee the simultaneous satisfaction of all composed
objectives. The compositional barrier functions are applied to the example of
ensuring collision avoidance and static/dynamical graph connectivity of teams
of mobile robots. The resulting composite safety and connectivity barrier
certificates are verified experimentally on a team of four mobile robots.Comment: To appear in 55th IEEE Conference on Decision and Control, December
12-14, 2016, Las Vegas, NV, US
Analysis of the Effects of Failure and Noise in the Distributed Connectivity Maintenance of a Multi-robot System
To perform cooperative tasks in a decentralized manner, multi-robot systems
are often required to communicate with each other. Therefore, maintaining the
communication graph connectivity is a fundamental issue when roaming a
territory with obstacles. However, when dealing with real-robot systems,
several sources of data corruption can appear in the agent interaction. In this
paper, the effects of failure and noise in the communication between agents are
analyzed upon a connectivity maintenance control strategy. The results show
that the connectivity strategy is resilient to the negative effects of such
disturbances under realistic settings that consider a bandwidth limit for the
control effort. This opens the perspective of applying the connectivity
maintenance strategy in adaptive schemes that consider, for instance,
autonomous adaptation to constraints other than connectivity itself, e.g.
communication efficiency and energy harvesting.Comment: 6 pages, 7 figures, published in CINTI 201
Suboptimal Event-Triggered Consensus of Multiagent Systems
In this paper the suboptimal event-triggered consensus problem of Multiagent systems is investigated. Using the combinational measurement approach, each agent only updates its control input at its own event time instants. Thus the total number of events and the amount of controller updates can be significantly reduced in practice. Then, based on the observation of increasing the consensus rate and reducing the number of triggering events, we have proposed the time-average cost of the agent system and developed a suboptimal approach to determine the triggering condition. The effectiveness of the proposed strategy is illustrated by numerical examples
Distributed Estimation and Control of Algebraic Connectivity over Random Graphs
In this paper we propose a distributed algorithm for the estimation and
control of the connectivity of ad-hoc networks in the presence of a random
topology. First, given a generic random graph, we introduce a novel stochastic
power iteration method that allows each node to estimate and track the
algebraic connectivity of the underlying expected graph. Using results from
stochastic approximation theory, we prove that the proposed method converges
almost surely (a.s.) to the desired value of connectivity even in the presence
of imperfect communication scenarios. The estimation strategy is then used as a
basic tool to adapt the power transmitted by each node of a wireless network,
in order to maximize the network connectivity in the presence of realistic
Medium Access Control (MAC) protocols or simply to drive the connectivity
toward a desired target value. Numerical results corroborate our theoretical
findings, thus illustrating the main features of the algorithm and its
robustness to fluctuations of the network graph due to the presence of random
link failures.Comment: To appear in IEEE Transactions on Signal Processin
Multi-objective compositions for collision-free connectivity maintenance in teams of mobile robots
Compositional barrier functions are proposed in this paper to systematically compose multiple objectives for teams of mobile robots. The objectives are first encoded as barrier functions, and then composed using AND and OR logical operators. The advantage of this approach is that compositional barrier functions can provably guarantee the simultaneous satisfaction of all composed objectives. The compositional barrier functions are applied to the example of ensuring collision avoidance and static/dynamical graph connectivity of teams of mobile robots. The resulting composite safety and connectivity barrier certificates are verified experimentally on a team of four mobile robots
Distributed constrained connectivity control for proximity networks based on a receding horizon scheme
info:eu-repo/semantics/publishe