Flight Path Planning for a Solar Powered UAV in Wind Fields Using Direct Collocation

Kim, Seong-Hwan; Padilla, Giancarlo Eder Guerra; Kim, Kun-Jung; Yu, Kee-Ho

doi:10.1109/taes.2019.2926654

Cited by 34 publications

(16 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The authors present the use of solar energy for UAVs in various weather conditions 38 (Figure 5). Several existing path planning algorithms are combined, and it is proposed to use wind energy in windy weather environments.…”

Section: Uav Path Planning Approachesmentioning

confidence: 99%

Aspects of unmanned aerial vehicles path planning: Overview and applications

Khan

Saad

et al. 2021

Int J Communication

View full text Add to dashboard Cite

Aiming to the applications from security surveillance, military operational capabilities to the content and package delivery, unmanned aerial vehicles (UAVs) has a successfully created his space in the available technologies. The compact sized powerful flying robots are wirelessly controlled and are capable to complete tasks with and without direct human intervention. UAVs however still face serious challenges that limit the dream of complete autonomous unmanned flying machines. The key challenges include path planning and obstacle avoidance of these unmanned flying robots that are unavoidable while performing the application-specific functionalities both in indoor and outdoor environments. In this manuscript with a survey, we investigate the state-of-the-art UAV path planning algorithms and obstacle avoidance techniques. We have also summarized and compared the schemes in tabular form. In addition, current and future research directions and challenges are also discussed, showing the prospective research directions.

show abstract

Section: Uav Path Planning Approachesmentioning

confidence: 99%

Aspects of unmanned aerial vehicles path planning: Overview and applications

Khan

Saad

et al. 2021

Int J Communication

View full text Add to dashboard Cite

show abstract

“…Hu [24] studied the influence of the flight altitude on the aircraft fuel efficiency and achieved the purpose of fuelsaving by controlling the flight altitude. Coombes and Kim [25], [26] considered the influence of the wind on the flight of rotorcraft and solved the path planning of the UAV by using a geometric method. Sun [27] investigated the resource allocation algorithm designed for multicarrier solar-powered UAV communication systems.…”

Section: B Uav Path Planning Under the Influence Of Meteorological Fmentioning

confidence: 99%

Meteorology-Aware Path Planning for the UAV Based on the Improved Intelligent Water Drops Algorithm

2021

View full text Add to dashboard Cite

A wide range of applications of the unmanned aerial vehicle (UAV) have been observed in the past few years, and path planning is one of the most critical issues that require to be resolved. UAVs are still prone to meteorological impediments such as thunderstorms, ice accumulation, and severe convective weather for the safety of flights. This paper proposes a meteorology-aware path planning method based on the improved intelligent water drops (IIWD) algorithm. The algorithm consists of both static and dynamic path planning. In the static path planning phase, ice accumulation and the Richardson number are considered when determining the trajectory with low risk. In the dynamic path planning phase, the latest forecast products are adopted to modify the planned path, and the virtual potential force is applied to adjust the flight direction of the UAV when encountered with severe convective weather. The validation and efficiency of the proposed algorithm are verified via simulations in comparison with the ant colony optimization, genetic algorithm, and Q-learning algorithm, where the quality of our algorithm's performance in terms of flight time and risk degree is determined. Meanwhile, the risk degree of the UAV flight path at different altitudes is analyzed. The simulation results show that the average flight speed decreases, and the risk degree increases along with the descending of the flight altitude, respectively, which is found to be in consensus with the theory of meteorology.INDEX TERMS meteorology-aware path planning, UAV, dynamic environment, improved intelligent water drops algorithm.

show abstract

“…[26] studies a distributed multiagent path planning algorithm for quadrotors in dynamic environments. An energy-based path planning framework is used to improve flight endurance for a solarpowered UAV in [27]. A multiobjective path planning is presented in [28] to design a feasible path for a UAV, where safety is considered in the proposed algorithm.…”

Section: Introductionmentioning

confidence: 99%

Path Planning and Control of a Quadrotor UAV Based on an Improved APF Using Parallel Search

Huang

Qin

et al. 2021

International Journal of Aerospace Engineering

View full text Add to dashboard Cite

Control and path planning are two essential and challenging issues in quadrotor unmanned aerial vehicle (UAV). In this paper, an approach for moving around the nearest obstacle is integrated into an artificial potential field (APF) to avoid the trap of local minimum of APF. The advantage of this approach is that it can help the UAV successfully escape from the local minimum without collision with any obstacles. Moreover, the UAV may encounter the problem of unreachable target when there are too many obstacles near its target. To address the problem, a parallel search algorithm is proposed, which requires UAV to simultaneously detect obstacles between current point and target point when it moves around the nearest obstacle to approach the target. Then, to achieve tracking of the planned path, the desired attitude states are calculated. Considering the external disturbance acting on the quadrotor, a nonlinear disturbance observer (NDO) is developed to guarantee observation error to exponentially converge to zero. Furthermore, a backstepping controller synthesized with the NDO is designed to eliminate tracking errors of attitude. Finally, comparative simulations are carried out to illustrate the effectiveness of the proposed path planning algorithm and controller.

show abstract

Flight Path Planning for a Solar Powered UAV in Wind Fields Using Direct Collocation

Cited by 34 publications

References 26 publications

Aspects of unmanned aerial vehicles path planning: Overview and applications

Aspects of unmanned aerial vehicles path planning: Overview and applications

Meteorology-Aware Path Planning for the UAV Based on the Improved Intelligent Water Drops Algorithm

Path Planning and Control of a Quadrotor UAV Based on an Improved APF Using Parallel Search

Contact Info

Product

Resources

About