Papers

LiDARFlow: Real-Time Panel-Based MAV Guidance in Unknown Environments

This preprint describes a lightweight onboard guidance system for micro aerial vehicles in unknown environments, combining a guiding vector field for nominal motion with panel-method potential-flow obstacle avoidance. In indoor flight tests at 0.5 m/s, a quadrotor using only a Livox MID-360 LiDAR and Raspberry Pi 5 successfully completed waypoint-navigation and direction-following tasks while avoiding all obstacles. The result matters because it shows map-free sense-and-avoid can run in real time on constrained onboard hardware, reducing operator workload for cluttered or emergency missions.