RVC-NMPC: Nonlinear Model Predictive Control with Reciprocal Velocity Constraints for Mutual Collision Avoidance in Agile UAV Flight

Fuente: arXiv
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Hauptverfasser: Kratky, Vit, Penicka, Robert, Gupta, Parakh M., Prochazka, Ondrej, Saska, Martin
Format: Preprint
Veröffentlicht: 2025
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author Kratky, Vit
Penicka, Robert
Gupta, Parakh M.
Prochazka, Ondrej
Saska, Martin
author_facet Kratky, Vit
Penicka, Robert
Gupta, Parakh M.
Prochazka, Ondrej
Saska, Martin
contents This paper presents an approach to mutual collision avoidance based on Nonlinear Model Predictive Control (NMPC) with time-dependent Reciprocal Velocity Constraints (RVCs). Unlike most existing methods, the proposed approach relies solely on observable information about other robots, eliminating the necessity of excessive communication use. The computationally efficient algorithm for computing RVCs, together with the direct integration of these constraints into NMPC problem formulation on a controller level, allows the whole pipeline to run at 100 Hz. This high processing rate, combined with modeled nonlinear dynamics of the controlled Uncrewed Aerial Vehicles (UAVs), is a key feature that facilitates the use of the proposed approach for an agile UAV flight. The proposed approach was evaluated through extensive simulations emulating real-world conditions in scenarios involving up to 10 UAVs and velocities of up to 25 m/s, and in real-world experiments with accelerations up to 30 m/s$^2$. Comparison with state of the art shows 31% improvement in terms of flight time reduction in challenging scenarios, while maintaining a collision-free navigation in all trials.
format Preprint
id arxiv_https___arxiv_org_abs_2512_08574
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle RVC-NMPC: Nonlinear Model Predictive Control with Reciprocal Velocity Constraints for Mutual Collision Avoidance in Agile UAV Flight
Kratky, Vit
Penicka, Robert
Gupta, Parakh M.
Prochazka, Ondrej
Saska, Martin
Robotics
This paper presents an approach to mutual collision avoidance based on Nonlinear Model Predictive Control (NMPC) with time-dependent Reciprocal Velocity Constraints (RVCs). Unlike most existing methods, the proposed approach relies solely on observable information about other robots, eliminating the necessity of excessive communication use. The computationally efficient algorithm for computing RVCs, together with the direct integration of these constraints into NMPC problem formulation on a controller level, allows the whole pipeline to run at 100 Hz. This high processing rate, combined with modeled nonlinear dynamics of the controlled Uncrewed Aerial Vehicles (UAVs), is a key feature that facilitates the use of the proposed approach for an agile UAV flight. The proposed approach was evaluated through extensive simulations emulating real-world conditions in scenarios involving up to 10 UAVs and velocities of up to 25 m/s, and in real-world experiments with accelerations up to 30 m/s$^2$. Comparison with state of the art shows 31% improvement in terms of flight time reduction in challenging scenarios, while maintaining a collision-free navigation in all trials.
title RVC-NMPC: Nonlinear Model Predictive Control with Reciprocal Velocity Constraints for Mutual Collision Avoidance in Agile UAV Flight
topic Robotics
url https://arxiv.org/abs/2512.08574