AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarms
This addresses safety concerns for autonomous systems in real-world applications, but it is incremental as it builds on existing AMLAS guidance.
The paper tackles the challenge of safety assurance for emergent behaviors in autonomous robotic swarms by proposing AERoS, a process based on AMLAS guidance, and demonstrates it through a case study of a robot swarm operating a public cloakroom.
The behaviours of a swarm are not explicitly engineered. Instead, they are an emergent consequence of the interactions of individual agents with each other and their environment. This emergent functionality poses a challenge to safety assurance. The main contribution of this paper is a process for the safety assurance of emergent behaviour in autonomous robotic swarms called AERoS, following the guidance on the Assurance of Machine Learning for use in Autonomous Systems (AMLAS). We explore our proposed process using a case study centred on a robot swarm operating a public cloakroom.