DISTRIBUTED COOPERATIVE CONTROL OF MULTIPLE VEHICLE FORMATIONS USING STRUCTURAL POTENTIAL FUNCTIONS

By Reza Olfati-Saber, Richard M. Murray. 2002

746 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/78cd295ae558a9c370b7636bd1a66e8ff9006cc5

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In Computer Networks and Communications

In Computer Vision and Pattern Recognition

In Control and Systems Engineering

Citations in the corpus

Local control strategies for groups of mobile autonomous agents (2004, background): “Besides being of interest in biology, Reynolds’ ideas have relevance in the subject of multiple vehicle formations, e.g., [20], [19], [ 15 ].”
Recent Research in Cooperative Control of Multivehicle Systems (2007, background): “Other work on the use of potential fields includes that of Olfati-Saber [33], who uses potential functions obtained from structural constraints of a desired formation in a way that leads to a collision-free, distributed, and bounded state feedback law for each vehicle.”
Swarm aggregations using artificial potentials and sliding-mode control (2005, background): “Some of the work we would like to mention here include the work by Desai and his colleagues in [21, 22], where the authors use graph theory to model a formation of robots navigating a terrain with obstacles, Egerstedt and coworkers in [23, 24], where the authors use a kinematic model for the robot m”
Coordination of groups of mobile autonomous agents using nearest neighbor rules (2002, background): “[9] and Olfati and Murray [10] use potential function theory to understand flocking behavior while Fax and Murray [11] and Desai et.”
Formation Tracking Control of Unicycle-Type Mobile Robots With Limited Sensing Ranges (2008, background): “, [2], [7], [11], [13], [14], and [17]) or fully actuated vehicles [6] (which can be converted to double-integrator dynamics via a feedback linearization) were investigated.”
Distributed Formation Control of Multi-Agent Systems Using Complex Laplacian (2014, background): “The former mainly concentrates on defining a formation using graph-theoretic rigidity [4], [16], [17], [22], [33], [40], while the latter concerns stabilization to a formation [7], [8], [10], [24], [32], [38], [39] and control of formation shape in moving [3], [5], [12]–[14], [20].”
Optimal scheduling for refueling multiple autonomous aerial vehicles (2006, background): “Stability analysis of multiple agents formation control via interaction topology has been studied in [21]–[24].”
Abstraction and control for Groups of robots (2004, background): “Given a vector field , the set of all vector fields which maps to is underdetermined.”
Stable flocking of mobile agents, part I: fixed topology (2003, background): “Similar problems have become a major thrust in systems and control theory, in the context of cooperative control, distributed control of multiple vehicles and formation control; see for example [16], [13], [ 21 ], [22], [5], [15], [7], [26], [11], [19].”
Flocking for multi-agent dynamic systems: algorithms and theory (2006, methodology): “Remark 1. The function kzk was eectively used in [ 32 ] as a penalty function in construction of potential function for formation control.”
Flocking with obstacle avoidance: cooperation with limited communication in mobile networks (2003, background): “Following the general idea of construction of potential/cost functions for structural graphs in [ 11 , 12], we deflne the following Hamiltonian as the structural energy of an fi-net (or fi-∞ock):”
Distance‐based undirected formations of single‐integrator and double‐integrator modeled agents in n‐dimensional space (2014, background): “1 The stability of undirected formations of double-integrator modeled agents has been studied in [10] on the basis of the LaSalle invariance principle.”
Necessary and sufficient graphical conditions for formation control of unicycles (2005, background): “In [21], formation stabilization of a group of agents with linear dynamics (double-integrator) is studied using structural potential functions.”