Distributed Source Seeking via a Circular Formation of Agents Under Communication Constraints

Abstract

Abstract-This paper addresses the source seeking problem in which a group of autonomous vehicles must locate and follow the source of some signal based on measurements of the signal strength at different positions. Based on the observation that the gradient of the signal strength can be approximated by a circular formation of agents via a simple weighted average of the signal measured by each agent, we propose a combination of a cooperative control law to stabilize the agents to a circular formation and a distributed consensus-based source seeking algorithm, which is guaranteed to steer the circular formation towards the vicinity of the source location. In particular, the proposed algorithm is provided with two tunable parameters that allow for a tradeoff between speed of convergence, noise filtering and formation stability. The benefit of using consensus-based algorithms resides in a more realist discrete time control of the agents and in asynchronous communication resilient to delays, which is particularly relevant for underwater applications. The analytic results are complemented with numerical simulations.

Adaptive Hessian Estimation Based Extremum Localization

“…Note that the base adaptive law (18) and the adaptive law (21) with parameter projections can be rewritten, respectively, asθ…”

Circular Formation Control of Multiagent Systems with Any Preset Phase Arrangement

“…Let G be a ring topology graph and * be its corresponding Laplacian matrix defined by (19). Consider model (1) with any initial conditions ( 0 ) and satisfying Assumption 1; under the circular motion control law (22) and phase control law (20), the agents are all enforced to converge to a circular formation of center and radius with phase arrangement by presetting * + and * − , for = 1, 2, .…”

“…The circular formation is a design method for steering the agents to orbit around a target along a common circle, which provides a simple geometric shape to collect data with a desired spatial and temporal distribution. In the community of systems and control, research efforts have been devoted to the circle formation problem for multiagent systems modeled as single or double integrators [14][15][16][17][18] and unicycles [19][20][21][22][23][24][25][26] under different communication topologies. Circular motion has been studied in the scenario of cyclic pursuit with ring topology [14][15][16][17][18][19][20][21][22][23].…”

Cooperative source seeking via networked multi-vehicle systems

“…In comparison with that of a scalar field, the use of multiple fields potentially increases the search reliability and efficiency. Although multi-vehicle systems have been employed in Frihauf et al (2014), Khong et al (2014), Brinon-Arranz et al (2016), Turgeman & Werner (2018), the seeking position therein is the source of only one scalar field and all the vehicles take samples from the same scalar field. Hence, the cooperation is essentially not indispensable and cannot be used to find the source of multiple scalar fields.…”