RADAR Perception for Dynamic Obstacle Avoidance onboard small-scale Quadrotor UAVs

2026-08-03

AI Summary

This work addresses the challenge of dynamic obstacle avoidance for small quadrotors during high-speed flight, particularly under adverse conditions such as abrupt illumination changes or smoke. It presents the first onboard, real-time collision avoidance system based on millimeter-wave radar. The proposed framework integrates a lightweight interacting multiple model (IMM) tracker with a control barrier function (CBF)-based controller in a perception-control co-design architecture that directly outputs collision-avoidance accelerations satisfying spatiotemporal constraints. The authors theoretically derive sufficient conditions guaranteeing successful avoidance. Experimental results demonstrate centimeter-level accuracy across 390 trials, with position errors below 0.15 m, 0.93 m, and 0.87 m in the x, y, and z axes, respectively, and an end-to-end latency of approximately 14 ms, enabling robust operation in both bright/dark transitions and smoky environments.

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).

Problem

• dynamic obstacle avoidance
• UAV
• mmWave RADAR
• perception latency
• sensing range

Innovation

• mmWave RADAR
• dynamic obstacle avoidance
• control-barrier functions
• interacting multiple models
• onboard perception