Nano-UAVs use Lévy walks to boost exploration by 79.6% without communication
New SDLW controller lets palm-sized drones explore complex spaces autonomously and collision-free.
Efficient autonomous exploration with palm-sized nano-UAVs remains challenging due to severe limitations in sensing, computation, and flight endurance. Researchers Wai Lun Leong and Teo Swee Huat Rodney present a lightweight sensor-driven Lévy walk (SDLW) controller for aerial robots weighing under 50 grams, equipped only with sparse local sensing. Each robot independently samples its Lévy exponent from a uniform prior and selects headings using a von Mises distribution that biases motion toward open directions—all without inter-robot communication. This emergent adaptive behavior preserves superdiffusive exploration properties while keeping computational cost constant.
Simulation results demonstrate substantial improvements: 79.6% better coverage in open arenas, 43.1% in rooms-and-corridors, and 13.6% in cluttered environments, with collision reductions of 13.0%, 7.1%, and 1.4% respectively relative to a uniform-heading baseline. The method provides a practical framework for scalable multi-robot exploration on minimal-sensing, resource-constrained nano-UAVs. The work has been accepted for publication in the Proceedings of the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026).
- No inter-robot communication required for exploration coordination, enabling scalable swarms.
- Coverage improvements up to 79.6% in open arenas and 43.1% in structured indoor environments.
- Collision reductions of 13.0% and 7.1% in open and corridor layouts respectively.
Why It Matters
Enables efficient, scalable swarm exploration with tiny drones for search-and-rescue, inspection, and surveillance.