Reducing planning time in swarm exploration via quorum sensing and discrete-event scheduling

This paper presents an event-driven framework for multi-agent exploration that couples a lightweight scheduler and blackboard with a Quorum Sensing (QS) coordination layer. Robots emit and sense a diffusive field using two scalar probes and a contact signal, select one of four motion primitives from local gradients, and make fully asynchronous, arrival-triggered decisions without global rounds. The QS field is integrated on a grid with explicit diffusion, decay, and no-flux obstacle boundaries, while motion uses arrival-time timestamps to reduce intermediate events and avoid idle time. Across six layouts (200300 cells) and swarms of 4–20 agents, the QS policy lowered planning time by about 33% and route imbalance by about 31% relative to an asynchronous non-QS baseline; average path length remained competitive and repeated length fell by roughly 17%. Ablations (no circumnavigation, fixed emissions, single-probe sensing) degraded at least one metric, clarifying the role of each mechanism, and scheduler wall-time scaled nearly linearly up to six threads. Because sensing and actuation are minimal and decisions are local, the controller maps cleanly to differential-drive robots and short-range signaling, enabling transfer to low-cost platforms while preserving reproducibility.