Autonomous Navigation and Obstacle Avoidance for a Wheeled Mobile Robots: A Hybrid Approach

Hacene, Nacer; Mendil, Boubekeur

doi:10.5120/14027-2285

Cited by 4 publications

(3 citation statements)

References 26 publications

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“…This method is also usable in an unknown environment. The gap-based online motion-planning algorithm has also been used with a Lidar sensor by introducing a binary sensing vector (the value of the vector element is equal to 1 if there is an obstacle in that direction) [12].…”

Section: Previous Workmentioning

confidence: 99%

Uncertain estimation-based motion-planning algorithms for mobile robots

Gyenes

Szadeczky-Kardoss

2021

ACTA IMEKO

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Collision-free motion planning for mobile agents is a challenging task, especially when the robot has to move towards a target position in a dynamic environment. The main aim of this paper is to introduce motion-planning algorithms using the changing uncertainties of the sensor-based data of obstacles. Two main algorithms are presented in this work. The first is based on the well-known velocity obstacle motion-planning method. In this method, collision-free motion must be achieved by the algorithm using a cost-function-based optimisation method. The second algorithm is an extension of the often-used artificial potential field. For this study, it is assumed that some of the obstacle data (e.g. the positions of static obstacles) are already known at the beginning of the algorithm (e.g. from a map of the enviroment), but other information (e.g. the velocity vectors of moving obstacles) must be measured using sensors. The algorithms are tested in simulations and compared in different situations.

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Section: Previous Workmentioning

confidence: 99%

Uncertain estimation-based motion-planning algorithms for mobile robots

Gyenes

Szadeczky-Kardoss

2021

ACTA IMEKO

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“…are proposed in literature. These path planning algorithms can be categorized into two based on the two aspects of completeness and the scope [1,[23][24][25][26][27][28]. From the completeness point of view, algorithms can be categorized as classical or heuristic.…”

Section: Introductionmentioning

confidence: 99%

“…Depending on the scope, path planning algorithms are classified into two broad categories -203 10.1515/jaiscr-2015-0028 Figure 1. Taxonomy of mobile robot path planning algorithms as global path planning (deliberative paradigm) and local path planning (reactive paradigm) [1,[23][24][25][26][27]. A basic hierarchical classification of the path planning algorithms is given in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

An Artificial Potential Field Based Mobile Robot Navigation Method To Prevent From Deadlock

Weerakoon

Ishii

Nassiraei

2015

Journal of Artificial Intelligence and Soft Computing Research

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Artificial Potential Filed (APF) is the most well-known method that is used in mobile robot path planning, however, the shortcoming is that the local minima. To overcome this issue, we present a deadlock free APF based path planning algorithm for mobile robot navigation. The Proposed-APF (P-APF) algorithm searches the goal point in unknown 2D environments. This method is capable of escaping from deadlock and non-reachability problems of mobile robot navigation. In this method, the effective front-face obstacle information associated with the velocity direction is used to modify the Traditional APF (T-APF) algorithm. This modification solves the deadlock problem that the T-APF algorithm often converges to local minima. The proposed algorithm is explained in details and to show the effectiveness of the proposed approach, the simulation experiments were carried out in the MATLAB environment. Furthermore, the numerical analysis of the proposed approach is given to prove a deadlock free motion of the mobile robot.

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The path planning method for anthropomorphic manipulator for avoidance an obstacle approximated by a parallelepiped

Петренко

Тебуева

Antonov

et al. 2020

IOP Conf. Ser.: Mater. Sci. Eng.

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There are various methods of planning paths for anthropomorphic manipulators that allow to bypass the obstacle and to work in real time. One of these methods was developed by the authors for circumventing an obstacle, which was approximated by a sphere. The approximation by a sphere of elongated obstacles overstates their size that leads to an excessive length of the path of avoiding the obstacle. The developed method combines analytical and numerical solutions with relatively low computational complexity, allowing it to work in real time. The effectiveness of the method is illustrated by a numerical example. The trajectory of the anthropomorphic manipulator required for its movement can be obtained using the existing methods of generating a trajectory based on the path of movement calculated using the proposed method. The developed method can be implemented in the systems of intellectual or supervisory control by anthropomorphic manipulators.

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Autonomous Navigation and Obstacle Avoidance for a Wheeled Mobile Robots: A Hybrid Approach

Cited by 4 publications

References 26 publications

Uncertain estimation-based motion-planning algorithms for mobile robots

Uncertain estimation-based motion-planning algorithms for mobile robots

An Artificial Potential Field Based Mobile Robot Navigation Method To Prevent From Deadlock

The path planning method for anthropomorphic manipulator for avoidance an obstacle approximated by a parallelepiped

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