Agree to Disagree: Consensus-Free Flocking under Constraints

TL;DR

This paper introduces a novel flocking control method that allows multi-agent systems to coordinate without shared goals or secure communication, using local observations and negotiation of constraints.

Contribution

It presents a new constrained collective potential function enabling negotiation of inter-agent parameters without global info or communication.

Findings

Effective in semi-trust scenarios with conflicting goals

Robust to lack of secure communication

Validated through extensive simulations

Abstract

Robots sometimes have to work together with a mixture of partially-aligned or conflicting goals. Flocking - coordinated motion through cohesion, alignment, and separation - traditionally assumes uniform desired inter-agent distances. Many practical applications demand greater flexibility, as the diversity of types and configurations grows with the popularity of multi-agent systems in society. Moreover, agents often operate without guarantees of trust or secure communication. Motivated by these challenges we update well-established frameworks by relaxing this assumption of shared inter-agent distances and constraints. Through a new form of constrained collective potential function, we introduce a solution that permits negotiation of these parameters. In the spirit of the traditional flocking control canon, this negotiation is achieved purely through local observations and does not require any global information or inter-agent communication. The approach is robust to semi-trust scenarios, where neighbouring agents pursue conflicting goals. We validate the effectiveness of the approach through a series of simulations.