Navigation of mobile robots in the presence of obstacles

Abiyev, Rahib H.; İbrahim, Dogan; Erin, B.

doi:10.1016/j.advengsoft.2010.08.001

Cited by 66 publications

(28 citation statements)

References 21 publications

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“…Abhiyev et al [1] have proposed a classical and fuzzy logic based algorithm for navigation mobile robot to avoid static obstacles in the environment. Raghuraman et al [2] have proposed a sensor based mobile robot navigation technique using fuzzy logic technique in indoor environment.…”

Section: Previous Workmentioning

confidence: 99%

Navigation of autonomous mobile robot using different activation functions of wavelet neural network

Panigrahi¹,

Ghosh²,

Parhi³

2015

Archives of Control Sciences

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An autonomous mobile robot is a robot which can move and act autonomously without the help of human assistance. Navigation problem of mobile robot in unknown environment is an interesting research area. This is a problem of deducing a path for the robot from its initial position to a given goal position without collision with the obstacles. Different methods such as fuzzy logic, neural networks etc. are used to find collision free path for mobile robot. This paper examines behavior of path planning of mobile robot using three activation functions of wavelet neural network i.e. Mexican Hat, Gaussian and Morlet wavelet functions by MATLAB. The simulation result shows that WNN has faster learning speed with respect to traditional artificial neural network.

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Section: Previous Workmentioning

confidence: 99%

Navigation of autonomous mobile robot using different activation functions of wavelet neural network

Panigrahi¹,

Ghosh²,

Parhi³

2015

Archives of Control Sciences

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“…[2][3][4][5][6] The formation control problem has been regarded as an important problem in the multi-robot system in order to accomplish cooperative tasks. The proposed formation control approaches have included the behavior-based approach, virtual structure approach, and leader-follower approach.…”

Section: Introductionmentioning

confidence: 99%

“…[16][17][18] Many authors have considered a controller with complete information of the environment. 3,4 Due to the complexity and uncertainty of the obstacle avoidance problem, classical obstacle avoidance methods, such as visibility graphs, 19 Voronoi diagrams, 20 cell decomposition, 21 and artificial potential fields, 22,23 were introduced. The use of the above algorithms for obstacle avoidance for mobile robot requires more time; they are complex and will not be completely feasible for real-time movement.…”

Section: Introductionmentioning

confidence: 99%

Obstacle avoidance behavior of swarm robots based on aggregation and disaggregation method

Chen

et al. 2017

SIMULATION

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One of the current challenges in the development of swarm robots is making them realize obstacle avoidance while keeping formation. This paper proposes a new obstacle avoidance method for multiple robots based on the aggregation and disaggregation approach. First, the formation-based multi-resolution models of swarm robots are presented and the formation attribute-based consistency mapping functions are designed. Then, obstacle avoidance behavior based on aggregation and disaggregation method is presented and the basic obstacle avoidance behaviors are designed. Finally, the simulation results are presented to show the feasibility of the proposed method.

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“…In global path planning, the surroundings are predefined and the path is known in advance. Conversely, in local path planning, the environment is unknown, and different types of modules are used to detect obstacles and avoid collisions [1].…”

Section: Introductionmentioning

confidence: 99%

An Optimal and Energy Efficient Multi-Sensor Collision-Free Path Planning Algorithm for a Mobile Robot in Dynamic Environments

et al. 2017

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There has been a remarkable growth in many different real-time systems in the area of autonomous mobile robots. This paper focuses on the collaboration of efficient multi-sensor systems to create new optimal motion planning for mobile robots. A proposed algorithm is used based on a new model to produce the shortest and most energy-efficient path from a given initial point to a goal point. The distance and time traveled, in addition to the consumed energy, have an asymptotic complexity of O(nlogn), where n is the number of obstacles. Real time experiments are performed to demonstrate the accuracy and energy efficiency of the proposed motion planning algorithm.

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Navigation of mobile robots in the presence of obstacles

Cited by 66 publications

References 21 publications

Navigation of autonomous mobile robot using different activation functions of wavelet neural network

Navigation of autonomous mobile robot using different activation functions of wavelet neural network

Obstacle avoidance behavior of swarm robots based on aggregation and disaggregation method

An Optimal and Energy Efficient Multi-Sensor Collision-Free Path Planning Algorithm for a Mobile Robot in Dynamic Environments

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