Multi-agent Coordination Under Spatio-Temporal And Communication Constraints

Master Student : Banjamin Bradin

Supervisor : Gregorio Marchesini

Multi-robot systems are essential in applications such as search and rescue, warehouse automation, and autonomous transportation, where tasks exceed the capabilities of a single agent. The effective collaboration of agents is critical, particularly in environments with communication constraints such as limited bandwidth, intermittent connectivity, and physical obstacles. This thesis aims to develop a framework for multi-robot systems that operate under these communication limitations, focusing on distributed task assignment and coordination. The proposed approach utilizes Signal Temporal Logic and Control Barrier Functions within a Quadratic Programming control framework to facilitate the indirect collaboration of agents by decomposing complex tasks into smaller sub-tasks. The framework incorporates a decentralized controller that optimizes control inputs to satisfy Signal Temporal Logic tasks while adhering to Control Barrier Function constraints. Validation is achieved through simulations and real-world experiments conducted in the Smart Mobility Lab at KTH, demonstrating that agents can achieve complex Signal Temporal Logic tasks despite limited communication. The findings contribute to enhancing the reliability and effectiveness of multi-robot systems in environments where communication is restricted.

The video shows a multi agent coordination problem, where a set of relay agents is helping pairs of non communicationg agnets acieve a relative formation in the absence of mutual communication.