Dual-UAV Payload Transportation Using Optimized Velocity Profiles via Real-Time Dynamic Programming
In this paper, a real-time dynamic programming (RTDP) approach was developed for the first time to jointly carry a slung load using two unmanned aerial vehicles (UAVs) with a trajectory optimized for time and energy consumption. The novel strategy applies RTDP algorithm, where the journey was discre...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/7/3/171 |
| _version_ | 1797612357740920832 |
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| author | Abdullah Mohiuddin Tarek Taha Yahya Zweiri Dongming Gan |
| author_facet | Abdullah Mohiuddin Tarek Taha Yahya Zweiri Dongming Gan |
| author_sort | Abdullah Mohiuddin |
| collection | DOAJ |
| description | In this paper, a real-time dynamic programming (RTDP) approach was developed for the first time to jointly carry a slung load using two unmanned aerial vehicles (UAVs) with a trajectory optimized for time and energy consumption. The novel strategy applies RTDP algorithm, where the journey was discretized into horizons consisting of distance intervals, and for every distance interval, an optimal policy was obtained using a dynamic programming sweep. The RTDP-based strategy is applied for dual-UAV collaborative payload transportation using coordinated motion where UAVs act as actuators on the payload. The RTDP algorithm provides the optimal velocity decisions for the slung load transportation to either minimize the journey time or the energy consumption. The RTDP approach involves minimizing a cost function which is derived after simplifying the combined model of the dual-UAV-payload system. The cost function derivation was also accommodated to dynamically distribute the load/energy between two multi-rotor platforms during a transportation mission. The cost function is used to calculate transition costs for all stages and velocity decisions. A terminal cost is used at the last distance interval during the first phase of the journey when the velocity at the end of the current horizon is not known. In the second phase, the last stage or edge of the horizon includes the destination, hence final velocity is known which is used to calculate the transition cost of the final stage. Once all transition costs are calculated, the minimum cost is traced back from the final stage to the current stage to find the optimal velocity decision. The developed approach was validated in MATLAB simulation, software in the loop Gazebo simulation, and real experiments. The numerical and Gazebo simulations showed the successful optimization of journey time or energy consumption based on the selection of the factor <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>λ</mi></mrow></semantics></math></inline-formula>. Both simulation and real experiments results show the effectiveness and the applicability of the proposed approach. |
| first_indexed | 2024-03-11T06:40:08Z |
| format | Article |
| id | doaj.art-b758328fc93346b1b8ccee78024535de |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-11T06:40:08Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-b758328fc93346b1b8ccee78024535de2023-11-17T10:39:26ZengMDPI AGDrones2504-446X2023-03-017317110.3390/drones7030171Dual-UAV Payload Transportation Using Optimized Velocity Profiles via Real-Time Dynamic ProgrammingAbdullah Mohiuddin0Tarek Taha1Yahya Zweiri2Dongming Gan3Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 1H9, CanadaDubai Future Foundation, Emirates Towers, Dubai P.O. Box 72127, United Arab EmiratesAdvanced Research and Innovation Center (ARIC), Aerospace Engineering Department, Khalifa University of Science and Technology, Abu Dhabi P.O. Box 127788, United Arab EmiratesPolytechnic Institute, Purdue University, Knoy 190, 401 North Grant Street, West Lafayette, IN 47907-2021, USAIn this paper, a real-time dynamic programming (RTDP) approach was developed for the first time to jointly carry a slung load using two unmanned aerial vehicles (UAVs) with a trajectory optimized for time and energy consumption. The novel strategy applies RTDP algorithm, where the journey was discretized into horizons consisting of distance intervals, and for every distance interval, an optimal policy was obtained using a dynamic programming sweep. The RTDP-based strategy is applied for dual-UAV collaborative payload transportation using coordinated motion where UAVs act as actuators on the payload. The RTDP algorithm provides the optimal velocity decisions for the slung load transportation to either minimize the journey time or the energy consumption. The RTDP approach involves minimizing a cost function which is derived after simplifying the combined model of the dual-UAV-payload system. The cost function derivation was also accommodated to dynamically distribute the load/energy between two multi-rotor platforms during a transportation mission. The cost function is used to calculate transition costs for all stages and velocity decisions. A terminal cost is used at the last distance interval during the first phase of the journey when the velocity at the end of the current horizon is not known. In the second phase, the last stage or edge of the horizon includes the destination, hence final velocity is known which is used to calculate the transition cost of the final stage. Once all transition costs are calculated, the minimum cost is traced back from the final stage to the current stage to find the optimal velocity decision. The developed approach was validated in MATLAB simulation, software in the loop Gazebo simulation, and real experiments. The numerical and Gazebo simulations showed the successful optimization of journey time or energy consumption based on the selection of the factor <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>λ</mi></mrow></semantics></math></inline-formula>. Both simulation and real experiments results show the effectiveness and the applicability of the proposed approach.https://www.mdpi.com/2504-446X/7/3/171UAVenergy optimizationdynamic programmingaerial transportationmulti-UAV systemRTDP |
| spellingShingle | Abdullah Mohiuddin Tarek Taha Yahya Zweiri Dongming Gan Dual-UAV Payload Transportation Using Optimized Velocity Profiles via Real-Time Dynamic Programming Drones UAV energy optimization dynamic programming aerial transportation multi-UAV system RTDP |
| title | Dual-UAV Payload Transportation Using Optimized Velocity Profiles via Real-Time Dynamic Programming |
| title_full | Dual-UAV Payload Transportation Using Optimized Velocity Profiles via Real-Time Dynamic Programming |
| title_fullStr | Dual-UAV Payload Transportation Using Optimized Velocity Profiles via Real-Time Dynamic Programming |
| title_full_unstemmed | Dual-UAV Payload Transportation Using Optimized Velocity Profiles via Real-Time Dynamic Programming |
| title_short | Dual-UAV Payload Transportation Using Optimized Velocity Profiles via Real-Time Dynamic Programming |
| title_sort | dual uav payload transportation using optimized velocity profiles via real time dynamic programming |
| topic | UAV energy optimization dynamic programming aerial transportation multi-UAV system RTDP |
| url | https://www.mdpi.com/2504-446X/7/3/171 |
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