Variable Time-Step MPC for Agile Multi-Rotor UAV Interception of Dynamic Targets

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 or intercepting dynamic targets. Agile planning using existing non-linear model predictive control methods is limited by the number of planning steps as it becomes increasingly computationally demanding. That reduces the prediction horizon length, leading to a decrease in solution quality. Besides, the fixed time-step length limits the utilization of the available UAV dynamics in the target neighborhood. In this letter, we propose to address these limitations by introducing variable time steps and coupling them with the prediction horizon length. A simplified point-mass 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 the presented 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.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2024-12-16
DOI
https://doi.org/10.1109/lra.2024.3518096
Citations
1
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
0.33
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article

Variable Time-Step MPC for Agile Multi-Rotor UAV Interception of Dynamic Targets

Martin Saska, František Nekovář, Jan Faigl, Atharva Ghotavadekar
1 citations
IEEE Robotics and Automation Letters
Advanced Control Systems Optimization
0.33
article

Variable Time-Step MPC for Agile Multi-Rotor UAV Interception of Dynamic Targets

Martin Saska, František Nekovář, Jan Faigl, Atharva Ghotavadekar
article en
1 citations

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 or intercepting dynamic targets. Agile planning using existing non-linear model predictive control methods is limited by the number of planning steps as it becomes increasingly computationally demanding. That reduces the prediction horizon length, leading to a decrease in solution quality. Besides, the fixed time-step length limits the utilization of the available UAV dynamics in the target neighborhood. In this letter, we propose to address these limitations by introducing variable time steps and coupling them with the prediction horizon length. A simplified point-mass 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 the presented 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.

IEEE Robotics and Automation LettersVol. 10(2)
Birla Institute of Technology and Science, Pilani - Goa Campus (IN), Czech Technical University in Prague (CZ)
Affordable and clean energy
Openalex Percentile: Top 38%
Advanced Control Systems Optimization
0.33
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Variable Time-Step MPC for Agile Multi-Rotor UAV Interception of Dynamic Targets — Martin Saska, František Nekovář, et al. · IEEE Robotics and Automation Letters (2024) | TGRS Research Map | TGRS