Robot navigation in unknown environment using fuzzy logic

Kumar, Neerendra; Tаkács, Marta; Vamossy, Zoltan

doi:10.1109/sami.2017.7880317

Cited by 24 publications

(9 citation statements)

References 9 publications

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“…Fuzzy logic can effectively manage its controlling actions even with imprecise sensory information [ 63 , 68 ]. In addition to that, fuzzy logic has been proven to be successful in coping with the navigation of robots in unknown environments [ 69 , 70 , 71 ]. Therefore, fuzzy logic is used to implement the subsystems for avoiding collisions with the sidewalls of drains during navigation.…”

Section: Fuzzy Logic System For Wall Collision Avoidancementioning

confidence: 99%

Collision Avoidance and Stability Study of a Self-Reconfigurable Drainage Robot

Parween

Muthugala

Heredia

et al. 2021

Sensors

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The inspection and maintenance of drains with varying heights necessitates a drain mapping robot with trained labour to maintain community hygiene and prevent the spread of diseases. For adapting to level changes and navigating in the narrow confined environments of drains, we developed a self-configurable hybrid robot, named Tarantula-II. The platform is a quadruped robot with hybrid locomotion and the ability to reconfigure to achieve variable height and width. It has four legs, and each leg is made of linear actuators and modular rolling wheel mechanisms with bi-directional movement. The platform has a fuzzy logic system for collision avoidance of the side wall in the drain environment. During level shifting, the platform achieves stability by using the pitch angle as the feedback from the inertial measuring unit (IMU) mounted on the platform. This feedback helps to adjust the accurate height of the platform. In this paper, we describe the detailed mechanical design and system architecture, kinematic models, control architecture, and stability of the platform. We deployed the platform both in a lab setting and in a real-time drain environment to demonstrate the wall collision avoidance, stability, and level shifting capabilities of the platform.

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Section: Fuzzy Logic System For Wall Collision Avoidancementioning

confidence: 99%

Collision Avoidance and Stability Study of a Self-Reconfigurable Drainage Robot

Parween

Muthugala

Heredia

et al. 2021

Sensors

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“…Collect odometer readings at the time of scan; X(g) ← X coordinate from odometer; Y(g) ← Y coordinate from odometer; 12:…”

Section: Problem Definition and Proposed Algorithmmentioning

confidence: 99%

“…However, the algorithm presented in [11] has the limitation that the robot may struck in the corners and may follow the same loop of the path again and again. A fuzzy controller for obstacle avoidance in unknown environment is presented in [12]. Although, the fuzzy rules, for the obstacles in the central part of the laser scan area, are right or left biased.…”

Section: Introductionmentioning

confidence: 99%

Robot navigation in unknown environment with obstacle recognition using laser sensor

Kumar

Vamossy

2019

IJECE

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<p>Robot navigation in unknown and dynamic environments may result in aimless wandering, corner traps and repetitive path loops. To address these issues, this paper presents the solution by comparing the standard deviation of the distance ranges of the obstacles appeared in the robot navigation path. For the similar obstacles, The standard deviations of distance range vectors, obtained from the laser range finder sensor of the robot at similar pose, are very close to each other. Therefore, the measurements of odometer sensor are also combined with the standard deviation to recognize the location of the obstacles. A novel algorithm, with obstacle detection feature, is presented for robot navigation in unknown and dynamic environments. The algorithm checks the similarity of the distance range vectors of the obstacles in the path and uses this information in combination with the odometer measurements to identify the obstacles and their locations. The experimental work is carried out using Gazebo simulator.</p>

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“…However, the algorithm presented in [7] has the limitation that the robot may struck in the corners and may follow the same loop of the path again and again. A fuzzy controller for obstacle avoidance in unknown environment is presented in [8]. Although, the fuzzy rules, for the obstacles in the central part of the laser scan area, are right or left biased.…”

Section: Introductionmentioning

confidence: 99%

Obstacle recognition and avoidance during robot navigation in unknown environment

Kumar

Vamossy

2018

IJET

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In this paper, firstly, a model for robot navigation in unknown environment is presented as a Simulink model. This model is applicable for obstacles avoidance during the robot navigation. However, the first model is unable to recognize the re-occurrences of the obstacles during the navigation. Secondly, an advanced algorithm, based on the standard deviations of laser scan range vectors, is proposed and implemented for robot navigation. The standard deviations of the lasers scans, robot positions and the time of scans with similar standard deviations are used to obtain the obstacle recognition feature. In addition to the obstacle avoidance, the second algorithm recognizes the re-appearances of the obstacles in the navigation path. Further, the obstacle recognition feature is used to break the repetitive path loop in the robot navigation. The experimental work is carried out on the simulated Turtlebot robot model using the Gazebo simulator.

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Robot navigation in unknown environment using fuzzy logic

Cited by 24 publications

References 9 publications

Collision Avoidance and Stability Study of a Self-Reconfigurable Drainage Robot

Collision Avoidance and Stability Study of a Self-Reconfigurable Drainage Robot

Robot navigation in unknown environment with obstacle recognition using laser sensor

Obstacle recognition and avoidance during robot navigation in unknown environment

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