Path planning for a UAV with kinematic constraints in the presence of polygonal obstacles

Maini, Parikshit; Sujit, P. B.

doi:10.1109/icuas.2016.7502625

Cited by 48 publications

(20 citation statements)

References 19 publications

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“…Figure 1 shows the densification result and the trajectory generated with that initial configuration. For the implementation of this improvement, the concept of visibility graphs is used as a principle, which consists in making a trajectory using the vertices of obstacles as points of the trajectory in a Euclidean space, in this way it is possible to avoid obstacles [3]. The Visibility Maps Algorithm consists of evaluating two distant nodes of the final path generated by the MBPF, measuring whether there is a risk of collision between the two nodes.…”

Section: Methodsmentioning

confidence: 99%

“…According to [5] the UAV are classified into three different categories, fixed wing, flapping wing and rotary wing, within this last category are the quadrotors, which are suitable for the application of algorithms that generate trajectories, due to their characteristics of easy control, low energy consumption, high flight safety and high maneuverability. For a quadrotor to perform missions autonomously requires algorithms for the planning of safe trajectories, this is a problem that has received considerable attention in recent years, proof of this are the recent studies on trajectories for UAV as they are those of [2], [3], [7], [8] among many others, such algorithms are efficient if they can obtain a solution, if any, to complex and disordered environments [1].…”

Section: Introductionmentioning

confidence: 99%

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Improvements of a three-dimensional trajectory planning algorithm for UAV navigation based on potential fields

Alberto¹,

Ardila²,

Pinzon³

2017

ces

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Path planning is a subject of wide interest in applications for unmanned aerial vehicles. A great variety of solutions have been generated to find paths free of collisions in three-dimensional scenarios, among them, the algorithm based on independent mobile points MBPF which uses the concept of artificial potential fields for the evasion of obstacles, is an algorithm that can be used in both 2D and 3D environments with static or dynamic obstacles and manages to avoid falling into local minimums. MBPF can find trajectories in a variety of complex 3D scenarios. However, it can be improved so that the trajectory reduces its distance, smooth the route and in some cases, converge. To improve the response of the algorithm, 3 improvements are proposed, one based on a modification to the original algorithm and another two based on a post processing of the result. the first improvement directly modifies the initial distribution of the starting points of the algorithm by densifying the points in the areas close to the obstacles, the two remaining improvements are made by post-processing the trajectory obtained for which Visibility Graphs are used and Active Contours. As a result, a considerable reduction 1572 Leonardo Ramírez Alberto et al. in the distance to be traveled is evidenced in the final trajectory and a greater smoothness is perceived in the curves.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improvements of a three-dimensional trajectory planning algorithm for UAV navigation based on potential fields

Alberto¹,

Ardila²,

Pinzon³

2017

ces

View full text Add to dashboard Cite

show abstract

“…Technical problems in the proposed approach Maini et al [23] The performance cannot be ensured in each scenario due to heavy reliance on specific maps. Overheads can increase exponential with the problem size.…”

Section: Refmentioning

confidence: 99%

Recent Developments in Path Planning for Unmanned Aerial Vehicles

Majeed¹,

Hwang²

2022

Motion Planning

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Unmanned aerial vehicles (UAVs) have demonstrated their effectiveness in performing diverse missions at significantly lower costs compared to the human beings. UAVs have the capabilities to reach and execute mission in those areas that are very difficult for humans to even reach such as forest, deserts, and mines. Integration of the latest technologies including reactive controls, sense and avoid, and onboard computations have strengthened their dominance further in various practical missions. Besides the innovative applications, the use of UAVs imposes several challenges, and one of those challenges is computing a low-cost path for aerial mission by avoiding obstacles as well as satisfying certain performance objectives (a.k.a path planning (PP)). To this end, this chapter provides a concise overview of various aspects concerning to PP including basics introduction of the subject matter, categorization of the PP approaches and problems, taxonomy of the essential components of the PP, performance objectives of the PP approaches, recent algorithms that have been proposed for PP in known and unknown environments, and future prospects of research in this area considering the emerging technologies. With this chapter, we aim to provide sufficient knowledge about one of the essential components of robotics technology (i.e., navigation) for researchers.

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“…Graph‐based search algorithms give the advantages of having fast searching abilities and possible online implementation, but they generate nonsmooth trajectories and they are not suitable for large areas. These methods have found wide applications in the UAV domain: Dijkstra's algorithm has been recently implemented in a fixed‐wing UAV and as a first step of a planning algorithm for UAV with kinematic constraints in the presence of polygonal obstacles; the A* approach, with a post‐smoothing process (A*PS) that finds significantly shorter paths than A*, and the LazyTheta* method, a 3D implementation of the Theta* algorithm using the line of sight function and applying smooth search, have been tested and compared with UAVs; D*‐Lite, a more efficient variant of A* that replans only a local section of the path, together with a Probabilistic Roadmap planner for building the environment's configuration and a smoothing process, has produced encouraging results with a simulated UAV …”

Section: Autonomous Navigationmentioning

confidence: 99%

Post‐disaster assessment with unmanned aerial vehicles: A survey on practical implementations and research approaches

Recchiuto

Sgorbissa

2017

Journal of Field Robotics

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In this paper, we provide a review of the principal aspects related to search & rescue (SAR) with unmanned aerial vehicles (UAVs), with particular interest in the phase of post-disaster assessment (PDA). Some areas of interest related to this topic have been chosen for the analysis: the aerial platforms used in the field, multirobot software architectures, onboard sensors and simultaneous localization and mapping approaches, terrain coverage algorithms, autonomous navigation techniques, and human-swarm interfaces. All these aspects have been analyzed with respect to the state-of-the-art, and also in relation to the project PRISMA, which focuses on the development and deployment of robots and autonomous systems that can operate in emergency scenarios, with a specific reference to monitoring and real-time intervention

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Path planning for a UAV with kinematic constraints in the presence of polygonal obstacles

Cited by 48 publications

References 19 publications

Improvements of a three-dimensional trajectory planning algorithm for UAV navigation based on potential fields

Improvements of a three-dimensional trajectory planning algorithm for UAV navigation based on potential fields

Recent Developments in Path Planning for Unmanned Aerial Vehicles

Post‐disaster assessment with unmanned aerial vehicles: A survey on practical implementations and research approaches

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