Multidepot Drone Path Planning With Collision Avoidance

Shen, Kun Yuan; Shivgan, Rutuja; Medina, Jorge; Dong, Ziqian; Rojas‐Cessa, Roberto

doi:10.1109/jiot.2022.3151791

Cited by 13 publications

(4 citation statements)

References 30 publications

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“…With an increasing number of drones being developed by different service providers, collision avoidance techniques need to be designed more carefully to ensure safe flights and successful parcel delivery and take-off. Thus, drone routes from other service providers should also be considered [ 14 , 62 ]. In [ 62 ], the authors proposed a centralized algorithm to find the collision free-path considering a congested flight space owing to the presence of other drones.…”

Section: Research and Development Challengesmentioning

confidence: 99%

“…Researchers have considered single drone-based delivery [ 9 ], truck-drone collaborative delivery [ 10 ], public transport and drone collaborative delivery [ 11 ], and multi-drone-based delivery with nearby CSs for multiple customers [ 12 ]. The overall trajectory or route planning to visit the customers/delivery points or CSs are derived as different variants of the travelling salesman problem (TSP) [ 10 , 12 , 13 , 14 ]. Many mathematical models such as mixed integer linear programming (MILP) [ 12 ], heuristic method [ 15 , 16 ], and reinforcement learning [ 6 ] have been adopted to obtain a sub-optimal solution under different objectives considering several constrains.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Drone Routing for Drone-Based Delivery Systems: A Review of Trajectory Planning, Charging, and Security

Raivi

Huda

Arafat

et al. 2023

Sensors

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Recently, owing to the high mobility and low cost of drones, drone-based delivery systems have shown considerable potential for ensuring flexible and reliable parcel delivery. Several crucial design issues must be considered to design such systems, including route planning, payload weight consideration, distance measurement, and customer location. In this paper, we present a survey of emerging drone routing algorithms for drone-based delivery systems, emphasizing three major drone routing aspects: trajectory planning, charging, and security. We focus on practical design considerations to ensure efficient, flexible, and reliable parcel delivery. We first discuss the potential issues arising when designing such systems. Next, we present a novel taxonomy based on the above-mentioned three aspects. We extensively review each algorithm for drone routing in terms of key features and operational characteristics. Furthermore, we compare the algorithms in terms of their main idea, advantages, limitations, and performance aspects. Finally, we present open research challenges to motivate further research in this field. In particular, we focus on the major aspects that researchers and engineers need to consider in order to design effective and reliable drone routing algorithms for drone-based delivery systems.

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Section: Research and Development Challengesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Drone Routing for Drone-Based Delivery Systems: A Review of Trajectory Planning, Charging, and Security

Raivi

Huda

Arafat

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…However, autonomy and intelligence are still lacking in these scenarios. As one of the key parts of UAV autonomous capability, the motion planning module plays an essential role in achieving full autonomy, which can provide a high-quality trajectory for UAV to generate safe and smooth motions [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Robust Planning System for Fast Autonomous Flight in Complex Unknown Environment Using Sparse Directed Frontier Points

Zhao

Dai

et al. 2023

Drones

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Path planning is one of the key parts of unmanned aerial vehicle (UAV) fast autonomous flight in cluttered environments. However, it remains a challenge to efficiently generate a high-quality trajectory for flight tasks with a high success rate. In this paper, a robust planning framework is proposed, which can stably support autonomous flight tasks in complex unknown environments with limited onboard computing resources. Firstly, we propose the directed frontier point information structure (DFP), which can roughly capture the frontier information of the explored environment. The planning direction of a local planner can be evaluated and rectified efficiently based on the DFP to avoid falling into traps with limited cost. Secondly, an adaptive fusion replanning method is designed to generate a high-quality trajectory efficiently by incorporating two optimization methods with different characteristics, which can both take advantage of different optimization methods while avoiding disadvantages as much as possible, but also adjust the focus of the optimization according to the actual situation to improve the success rate of the planning method. Finally, sufficient comparison and evaluation experiments in simulation environments are presented. Experimental results show the proposed method has better performance, especially in terms of adaptability and robustness, compared to typical and state-of-the-art methods in unknown complex scenarios. Moreover, the proposed system is integrated into a fully autonomous quadrotor, and the effectiveness of the proposed method is further evaluated by using the quadrotor in real-world environments.

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“…However, practical constraints such as the distance for collision avoidance and the distance for communication connection were not considered in the aforementioned researches. Specifically, there can be collisions among UAVs with high probability when they get closer, and the communication between UAVs may be interrupted when their distance becomes farther [18,19]. To achieve formation reconfiguration while satisfying such constraints, most researches have formulated the reconfiguration process as an optimization problem.…”

Section: Introductionmentioning

confidence: 99%

Reconfiguration for UAV Formation: A Novel Method Based on Modified Artificial Bee Colony Algorithm

Yang,

Mao

et al. 2023

Drones

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The flight formation of unmanned aerial vehicles (UAVs) needs to be reconfigured whenever necessary to cope with complex environments and varying tasks. However, the continuity, nonlinearity and high dimensionality of the UAV formation control parameters bring significant challenges to the efficiency and safety of UAV formation reconfiguration. To this end, this paper proposes a reconfiguration strategy of the UAV formation based on a modified Artificial Bee Colony (ABC) algorithm, which ensures superior efficiency and safety level simultaneously. Specifically, we first formulate the formation reconfiguration problem minimizing the time consumed for reconfiguration under the constraints of safety and connection. Then the continuous optimization problem is discretized by using the control parameterization and time discretization (CPTD) method. Finally, we use a modified ABC algorithm to find the solution of formation reconfiguration. Extensive performance evaluations are conducted to verify the superiority of the proposed method. It is concluded that the proposed algorithm achieves a better performance than the existing approaches in literature in solving the problem of 3-D formation reconfiguration.

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Multidepot Drone Path Planning With Collision Avoidance

Cited by 13 publications

References 30 publications

Drone Routing for Drone-Based Delivery Systems: A Review of Trajectory Planning, Charging, and Security

Drone Routing for Drone-Based Delivery Systems: A Review of Trajectory Planning, Charging, and Security

Robust Planning System for Fast Autonomous Flight in Complex Unknown Environment Using Sparse Directed Frontier Points

Reconfiguration for UAV Formation: A Novel Method Based on Modified Artificial Bee Colony Algorithm

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