Embedded Hierarchical MPC for Autonomous Navigation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F25%3A00383799" target="_blank" >RIV/68407700:21730/25:00383799 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/TRO.2025.3567529" target="_blank" >https://doi.org/10.1109/TRO.2025.3567529</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TRO.2025.3567529" target="_blank" >10.1109/TRO.2025.3567529</a>
Alternative languages
Result language
angličtina
Original language name
Embedded Hierarchical MPC for Autonomous Navigation
Original language description
To efficiently deploy robotic systems in society, mobile robots must move autonomously and safely through complex environments. Nonlinear model predictive control (MPC) methods provide a natural way to find a dynamically feasible trajectory through the environment without colliding with nearby obstacles. However, the limited computation power available on typical embedded robotic systems, such as quadrotors, poses a challenge to running MPC in real time, including its most expensive tasks: constraints generation and optimization. To address this problem, we propose a novel hierarchical MPC scheme that consists of a planning and a tracking layer. The planner constructs a trajectory with a long prediction horizon at a slow rate, while the tracker ensures trajectory tracking at a relatively fast rate. We prove that the proposed framework avoids collisions and is recursively feasible. Furthermore, we demonstrate its effectiveness in simulations and lab experiments with a quadrotor that needs to reach a goal position in a complex static environment. The code is efficiently implemented on the quadrotor's embedded computer to ensure real-time feasibility. Compared to a state-of-the-art single-layer MPC formulation, this allows us to increase the planning horizon by a factor of 5, which results in significantly better performance.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Robotics
ISSN
1552-3098
e-ISSN
1941-0468
Volume of the periodical
41
Issue of the periodical within the volume
May
Country of publishing house
US - UNITED STATES
Number of pages
19
Pages from-to
3556-3574
UT code for WoS article
001504037100001
EID of the result in the Scopus database
2-s2.0-105004592658