RADAR Perception for Dynamic Obstacle Avoidance onboard small-scale Quadrotor UAVs
2026-08-03 • Robotics
Robotics
AI summaryⓘ
The authors developed a system that helps small flying drones avoid obstacles quickly using special radar technology. They studied how sensing distance, speed, and control delay affect the drone's ability to dodge obstacles. Their system tracks moving objects and decides how the drone should move to avoid collisions, achieving very accurate positioning in tests, even in smoke or low visibility. They also showed it works fast enough on a small onboard computer, making it practical for real-time flying drones.
dynamic obstacle avoidanceUAVmmWave RADARcontrol-barrier functionsinteracting multiple modelslatencyreal-time controlposition tracking
Authors
Dnyandeep Mandaokar, Bernhard Rinner
Abstract
Fast dynamic obstacle avoidance (DOA) on uncrewed aerial vehicles (UAVs) demands not only low-latency control and actuation but also reliable perception with sufficient sensing range for accurate obstacle detection and speed estimation. This letter presents, to the best of our knowledge, the first mmWave RADAR-based perception-and-control system for fast onboard DOA. We derive and analyze latency and spatial bounds that relate sensing range, relative speed, and control delay, yielding sufficient conditions for successful avoidance. Our system adopts a lightweight tracker based on interacting multiple models and a controller based on control-barrier functions that directly outputs evasive accelerations. It achieves position errors of less than 0.15 m, 0.93 m, and 0.87 m in x, y, and z directions for 300 experiments with three different object sizes and varying visibility (light and dark), and a similar spread for 90 experiments in smoke. An onboard implementation on a Raspberry Pi 4B demonstrates real-time feasibility with an end-to-end sensing-to-command latency of approximately 14 ms. Code and the full dataset of 390 throws are available (https://tinyurl.com/radardoagit).