Collision Avoidance Mechanism for Symmetric Circular Formations of Unitary Mass Autonomous Vehicles at Constant Speed

Abstract

Collective motion is a promising field that studies how local interactions lead groups of individuals to global behaviors. Biologists try to understand how those subjects interplay in nature, and engineers are concerned with the application of interaction strategies to mobile vehicles, satellites, robots, etc. There are several models in literature that employ strategies observed in groups of beings in nature. The aim is not to literally mimic them but to extract suitable strategies for the chosen application. These models, constituted of multiple mobile agents, can be used in tasks such as data collection, surveillance and monitoring. One approach is to use phasecoupled oscillators to design the mobile agents, in which each member is an oscillator and they are coupled according to an interconnection network. This design usually does not keep track and handle the possible collisions within the group, and real applications obviously must manage these situations to prevent the equipment from crashing. This paper introduces a collision avoidance mechanism to a model of particles with phase-coupled oscillators dynamics for symmetric circular formations.

Graphical and Analytical Approaches for Analyzing Collective Behavior of Dynamic Multi-Agent Systems Governed by Generalized Cyclic Pursuit Mechanism

“…In the GCP law (2), let be k p = 0.4807, g p = 0.2300, and θ = 1.0747(rad). Then, the eigenvalues of the interconnection matrix A in (5) are obtained from (7), as illustrated in Figure 3(a). Because a pair of eigenvalues exists in the right-half-plane (RHP), the single-integratorlike agents of the multi-agent system, shown in Figure 2(a), diverge considerably from their expected behavior, which indicates that stability is not achieved.…”

“…This strategy is frequently used in cases where multiple agents must move in a coordinated manner, for instance, to entrap a target, conduct patrolling and surveillance operations, and seek sources in a sensed environment (see [1] and the references therein). The method-based classification of schemes implemented in circular formation control is as follows: leader-follower method [2][3][4], artificial potential method [5], behavior-based method [6,7], virtual structure method [8,9], event-triggered control method [10], and cyclic pursuit method [11][12][13][14][15][16][17][18][19][20]. Among these schemes, the cyclic pursuit method has attracted considerable attention because of its intrinsic benefits resulting from its minimal communication requirements for connectivity.…”

A Survey on Techniques in the Circular Formation of Multi-Agent Systems

“…Behavior-based Method [33,45,57,81,94,95,98,115] • Multiple expected and desired behavior is prescribed for every agent such as collision avoidance, obstacle avoidance, formation reconfiguration, target tracking, etc.…”

“…It is shown that the collision avoidance is guaranteed if the solution of system (2) satisfies z i − z j > 0 for any pair i, j, i = j, t > 0 and the order preservation is achieved. The research study [95] proposed a collision avoidance strategy with phase-coupled oscillators dynamics to achieve the symmetric circular formations without collision. This problem is studied in networking techniques, such as ring topology, etc.…”

“…This makes arbitrary distribution-based CFP more application-oriented. Based on the aforementioned observations, the CFP methods are classified as: Artificial potential method [89,90], cyclic pursuit method [91,92], leader-follower method [93], behavior-based method [94,95], and virtual structure method [96,97]. The comparison of mentioned methodologies is summarized in Table 2.…”