Path Following Control Tuning for an Autonomous Unmanned Quadrotor Using Particle Swarm Optimization

Rendón, Manuel A.; Martins, Felipe F.

doi:10.1016/j.ifacol.2017.08.054

Cited by 17 publications

(8 citation statements)

References 10 publications

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“…As shown in Figure 10, the basic PSO concept is specifcally based on their placement and velocity in the search area. Te PSO is used in numerous felds of mobile robot path planning for navigation by a humanoid robot [70], an industrial robot [71], a wheeled robot [72], an aerial robot [73], and an underwater robot [74] in an unknown and complex 3D environment. Zhang and Li [75] applied PSO to the mobile robot in the dynamic environment to optimize its travel time.…”

Section: Neural Networkmentioning

confidence: 99%

A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots

Rafai

Adzhar

Jaini

2022

Journal of Robotics

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Mobile robots have been widely used in various sectors in the last decade. A mobile robot could autonomously navigate in any environment, both static and dynamic. As a result, researchers in the robotics field have offered a variety of techniques. This paper reviews the mobile robot navigation approaches and obstacle avoidance used so far in various environmental conditions to recognize the improvement of path planning strategists. Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). Classical approaches have limitations of trapping in local minima, failure to handle uncertainty, and many more. On the other hand, it is observed that heuristic approaches can solve most real-world problems and perform well after some modification and hybridization with classical techniques. As a result, many methods have been established worldwide for the path planning strategy for mobile robots. The most often utilized approaches, on the other hand, are offered below for further study.

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Section: Neural Networkmentioning

confidence: 99%

A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots

Rafai

Adzhar

Jaini

2022

Journal of Robotics

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“…This method has been implemented for navigation of an aerial robot in three dimensional unknown environments [19], humanoid robot [20] and in industrial robot [21].…”

Section: Particle Swarm Optimization Approach (Pso)mentioning

confidence: 99%

A Review on Autonomous Mobile Robot Path Planning Algorithms

Adzhar¹,

Yuhani²,

Ahmad³

2020

Adv. sci. technol. eng. syst. j.

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The emerging trend of modern industry automation requires intelligence to be embedded into mobile robot for ensuring optimal or near-optimal solutions to execute certain task. This yield to a lot of improvement and suggestions in many areas related to mobile robot such as path planning. The purpose of this paper is to review the mobile robots path planning problem, optimization criteria and various methodologies reported in the literature for global and local mobile robot path planning. In this paper, commonly use classical approaches such as cell decomposition (CD), roadmap approach (RA), artificial potential field (AFP), and heuristics approaches such as genetic algorithm (GA), particle swarm optimization (PSO) approach and ant colony optimization (ACO) method are considered. It is observed that when it comes to dynamic environment where most of the information are unknown to the mobile robots before starting, heuristics approaches are more popular and widely used compared to classical approaches since it can handle uncertainty, interact with objects and making quick decision. Finally, few suggestions for future research work in this field are addressed at the end of this paper.

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“…The centripetal forces ω B × (Iω B ), the angular acceleration of the inertia (Iω B ), and the gyroscopic forces are equal to the total external torque τ B over the body frame. Afterwards, the governing equations for rotational motion can be summarized as 4 and I r is the rotor inertia moment. The transformation matrix W −1 η is used to convert the angular accelerations from the body frame into the inertial frame.…”

Section: Quadrotor Dynamics and Kinematicsmentioning

confidence: 99%

“…The study of the kinematics and dynamics of the quadrotor is the starting point for all of the researches, but more complicated aerodynamic effects of the rotors have been introduced as well. 4,5 Benic et al presented the complexity of the quadcopter mathematical model derivation. The influences of various parameters on quadcopter behavior are modeled from the aspects of physics and mathematics.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planning of Quadrotor Systems for Various Objective Functions

Heidari

Saska

2020

Robotica

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SUMMARY Quadrotors are unmanned aerial vehicles with many potential applications ranging from mapping to supporting rescue operations. A key feature required for the use of these vehicles under complex conditions is a technique to analytically solve the problem of trajectory planning. Hence, this paper presents a heuristic approach for optimal path planning that the optimization strategy is based on the indirect solution of the open-loop optimal control problem. Firstly, an adequate dynamic system modeling is considered with respect to a configuration of a commercial quadrotor helicopter. The model predicts the effect of the thrust and torques induced by the four propellers on the quadrotor motion. Quadcopter dynamics is described by differential equations that have been derived by using the Newton–Euler method. Then, a path planning algorithm is developed to find the optimal trajectories that meet various objective functions, such as fuel efficiency, and guarantee the flight stability and high-speed operation. Typically, the necessary condition of optimality for a constrained optimal control problem is formulated as a standard form of a two-point boundary-value problem using Pontryagin’s minimum principle. One advantage of the proposed method can solve a wide range of optimal maneuvers for arbitrary initial and final states relevant to every considered cost function. In order to verify the effectiveness of the presented algorithm, several simulation and experiment studies are carried out for finding the optimal path between two points with different objective functions by using MATLAB software. The results clearly show the effect of the proposed approach on the quadrotor systems.

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Path Following Control Tuning for an Autonomous Unmanned Quadrotor Using Particle Swarm Optimization

Cited by 17 publications

References 10 publications

A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots

A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots

A Review on Autonomous Mobile Robot Path Planning Algorithms

Trajectory Planning of Quadrotor Systems for Various Objective Functions

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