Real-Time Obstacle-Avoiding Path Planning for Mobile Robots

Choi, Ji-wung; Curry, Renwick E.; Elkaim, Gabriel Hugh

doi:10.2514/6.2010-8411

Cited by 22 publications

(8 citation statements)

References 7 publications

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“…These methods are sample-based and create random nodes toward the general direction of the goal vertex. One downfall to most of these real-time planning techniques is they require the user to recompute a solution when new information is presented [31,33]. Often this can be computationally difficult and not very realistic to do online (especially in complex environments).…”

Section: Literature Reviewmentioning

confidence: 99%

Fuzzy Logic Unmanned Air Vehicle Motion Planning

Sabo

Cohen

2012

Advances in Fuzzy Systems

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There are a variety of scenarios in which the mission objectives rely on an unmanned aerial vehicle (UAV) being capable of maneuvering in an environment containing obstacles in which there is little prior knowledge of the surroundings. With an appropriate dynamic motion planning algorithm, UAVs would be able to maneuver in any unknown environment towards a target in real time. This paper presents a methodology for two-dimensional motion planning of a UAV using fuzzy logic. The fuzzy inference system takes information in real time about obstacles (if within the agent's sensing range) and target location and outputs a change in heading angle and speed. The FL controller was validated, and Monte Carlo testing was completed to evaluate the performance. Not only was the path traversed by the UAV often the exact path computed using an optimal method, the low failure rate makes the fuzzy logic controller (FLC) feasible for exploration. The FLC showed only a total of 3% failure rate, whereas an artificial potential field (APF) solution, a commonly used intelligent control method, had an average of 18% failure rate. These results highlighted one of the advantages of the FLC method: its adaptability to complex scenarios while maintaining low control effort.

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Section: Literature Reviewmentioning

confidence: 99%

Fuzzy Logic Unmanned Air Vehicle Motion Planning

Sabo

Cohen

2012

Advances in Fuzzy Systems

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“…It is worth mentioning the work of Choi et al [38][39][40][41][42][43][44][45][46] related to the computation of trajectories of mobile robots designed from Bézier curves. In many of the publications, a constrained optimization problem is raised, where the function to be optimized is the curvature of a Bézier curve.…”

Section: Trajectories Of Mobile Robots Defined By Bézier Curvesmentioning

confidence: 99%

Path Planning Based on Parametric Curves

Pérez¹,

Aguilar²,

MontésSánchez³

et al. 2018

Advanced Path Planning for Mobile Entities

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Parametric curves are extensively used in engineering. The most commonly used parametric curves are, Bézier, B-splines, (NURBSs), and rational Bézier. Each and every one of them has special features, being the main difference between them the complexity of their mathematical definition. While Bézier curves are the simplest ones, B-splines or NURBSs are more complex. In mobile robotics, two main problems have been addressed with parametric curves. The first one is the definition of an initial trajectory for a mobile robot from a start location to a goal. The path has to be a continuous curve, smooth and easy to manipulate, and the properties of the parametric curves meet these requirements. The second one is the modification of the initial trajectory in real time attending to the dynamic properties of the environment. Parametric curves are capable of enhancing the trajectories produced by path planning algorithms adapting them to the kinematic properties of the robot. In order to avoid obstacles, the shape modification of parametric curves is required. In this chapter, an algorithm is proposed for computing an initial Bézier trajectory of a mobile robot and subsequently modifies it in real time in order to avoid obstacles in a dynamic environment.

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“…But in reality the threat of a circle was often an estimate of the inexact value, which made the missile's penetration difficult. The path of the mobile robot was planned in a high safe way by using the Voronoi diagram and the Bezier curve 10 . Applying this approach to the planning of anti-ship missile, it would improve the safety of missile path to a large extent without knowing the radius of the circle accurately.…”

Section: Introductionmentioning

confidence: 99%

Path Planning of Anti ship Missile based on Voronoi Diagram and Binary Tree Algorithm

2019

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The path planning of anti-ship missile should be considered both cruising in safety and striking in quick, which is an intractable problem. In particular, it is difficult to consider the safety of each missile path in the path planning of multiple missiles. To solve this problem, the “AREA Algorithm” is presented to divide the relative relations of areas：relative security area of the threat areas and fast-attack area of target approaching. Specifically，it is a way to achieve area division through the relationship between the target and the center of the operational area. The Voronoi diagram topology network, Dijkstra algorithm and binary tree algorithm have been used in the above process as well. Finally, Simulations have verified the feasibility and obvious advantages of “AREA Algorithm” compared with the single algorithm, and the tactical meaning in path planning of multiple missiles.

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Real-Time Obstacle-Avoiding Path Planning for Mobile Robots

Cited by 22 publications

References 7 publications

Fuzzy Logic Unmanned Air Vehicle Motion Planning

Fuzzy Logic Unmanned Air Vehicle Motion Planning

Path Planning Based on Parametric Curves

Path Planning of Anti ship Missile based on Voronoi Diagram and Binary Tree Algorithm

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