A robot swarm performs worse when you give it more direct control over its individual members.
Engineers typically believe that more actuation and better control lead to superior performance in complex systems. This resource allocation paradox shows that adding direct control to agents in a stochastic environment can degrade swarm coordination. The noise and delay in the system turn better individual control into a source of collective chaos. Optimal performance requires a counterintuitive balance of sparse actuation rather than constant intervention. This finding will change how we design autonomous fleets of drones or warehouse robots.
Controlling the Swarm: Sparse Actuation and Collision Avoidance under Stochastic Delay
arXiv · 2605.00395
Classical flocking models demonstrate how local interactions generate emergent order, but real-world multi-agent deployments are bound by severe constraints: limited actuator availability, heterogeneous communication latencies, and environmental noise. In this talk, we present a unified finite-N framework that tackles the interplay of these exact mechanisms. We study a delayed stochastic leader-follower particle system featuring topological communication, singular repulsion, and bounded sparse l