Variable Time-step MPC for Agile Multi-rotor UAV
Interception of Dynamic Targets

Atharva Ghotavadekar, František Nekovář, Martin Saska and Jan Faigl

Abstract

Agile trajectory planning can improve the efficiency of multi-rotor Uncrewed Aerial Vehicles (UAVs) in scenarios with combined task-oriented and kinematic trajectory planning, such as monitoring spatio-temporal phenomena with intercepting dynamic targets.
Agile planning using existing non-linear model predictive control methods is limited by the number of planning steps because, becoming increasingly computationally demanding.
This reduces the prediction horizon length, which leads to decrease in solution quality.
Besides, the fixed length time-step limits utilization of the available UAV dynamics in the target neighborhood.
In this paper, we propose to address these limitations by introducing variable time-steps and coupling them with the prediction horizon length.
A simplified mass-point motion primitive is used to leverage the differential flatness of quadrotor dynamics and the generation of feasible trajectories in the flat output space.
Based on evaluation results and experimentally validated deployment, the proposed method increases the solution quality by enabling planning for long flight segments but allowing tightly sampled maneuvering.

Paper link

https://ieeexplore.ieee.org/document/10803033

Source code

https://github.com/Atharva-05/vt_mpc

ArXiv

https://arxiv.org/abs/2503.14184