A Fuzzy-Logic-Based Approach for Mobile Robot Path Tracking

Antonelli, Gianluca; Chiaverini, Stefano; Fusco, Giuseppe

doi:10.1109/tfuzz.2006.879998

Cited by 205 publications

(125 citation statements)

References 29 publications

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“…The different fuzzy rule-based controller has been constructed to deal with different behavior and also helps the robot to get out from the trapped situations. Antonelli et al [50] have presented the path-following approach for differential drive mobile robots using the fuzzy logic technique. The designed fuzzy rules are able to emulate the human driving behavior.…”

Section: Hybridization Of Fuzzy and Nondeterministic Algorithmmentioning

confidence: 99%

Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review

Pandey¹

2017

IRATJ

178

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Mobile robot is an autonomous agent capable of navigating intelligently anywhere using sensor-actuator control techniques. The applications of the autonomous mobile robot in many fields such as industry, space, defence and transportation, and other social sectors are growing day by day. The mobile robot performs many tasks such as rescue operation, patrolling, disaster relief, planetary exploration, and material handling, etc. Therefore, an intelligent mobile robot is required that could travel autonomously in various static and dynamic environments. Several techniques have been applied by the various researchers for mobile robot navigation and obstacle avoidance. The present article focuses on the study of the intelligent navigation techniques, which are capable of navigating a mobile robot autonomously in static as well as dynamic environments. Keywords: IntroductionThis article introduces the literature survey of the various techniques used for mobile robot navigation. Navigation and obstacle avoidance are one of the fundamental problems in mobile robotics, which are being solved by the various researchers in the past two decades. The aim of navigation is to search an optimal or suboptimal path from the start point to the goal point with obstacle avoidance competence. Basically, the mobile robot navigation has been done by the Deterministic algorithm and Nondeterministic (Stochastic) algorithm. Nowadays, the hybridization of both the algorithms called as an Evolutionary algorithm is being used to solve the mobile robot navigation problem. Figure 1 shows the general classification of the Deterministic algorithm, Nondeterministic (Stochastic) algorithm, and Evolutionary algorithm, which are implemented for mobile robot navigation by various authors.

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Section: Hybridization Of Fuzzy and Nondeterministic Algorithmmentioning

confidence: 99%

Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review

Pandey¹

2017

IRATJ

178

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“…One of the critical problems is path-tracking robots, which includes a variety of theories and technologies such as ultrasonic mapping and vision systems. Indeed, the process that deals with this complex problem involved handles many issues including acquisition and processing of sensory data, decision making, trajectory planning, and motion control [1]. In addition, it is difficult to accurately model the interaction between the ground and the robot.…”

Section: Figure 1 Wheeled-drive Mobile Robot Prototypementioning

confidence: 99%

“…Intelligent techniques provide a promising approach to solve the issue of motion control with capacity of no longer relying on mathematical models and getting out of the linear constraints. In [1,2,[10][11][12], the authors proposed fuzzy logic method to overcome nonlinearities, and uncertainties of the system model. However, fuzzy controllers cannot be totally summarized for influence by the subjective factors of a person, in addition, the steady state error is hard to be eliminated, and this affects the quality of control.…”

Section: Figure 1 Wheeled-drive Mobile Robot Prototypementioning

confidence: 99%

“…There are several approaches that determine which information is. In [1,14,24], the authors estimated the parameters such as the value of curvature in the bend ahead of the mobile, the lateral error and the heading error. However, with an unknown path/line, the estimation of the value of curvature is very difficult and time consuming.…”

Section: Generating Vision System Outputmentioning

confidence: 99%

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Vision Based Autonomous Path/Line Following of a Mobile Robot Using a Hybrid Fuzzy PID Controller

Thuy¹,

Cường²

2016

Tuyển Tập Công Trình HNKH Toàn Quốc Lần Thứ 3 Về Điều Khiển &Amp; Tự Động Hoá VCCA - 2015

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Hội nghị toàn quốc lần thứ 3 về Điều khiển và Tự động hoá -VCCA-2015 VCCA-2015Rôbốt di động bám quỹ đạo tự động dựa trên xử lý ảnh sử dụng bộ điều khiển lai PID-mờ Tóm tắtTrong bài báo này, chúng tôi đề xuất một phương pháp điều khiển cho robốt tự hành để bám quỹ đạo cho trước trong môi trường trong nhà. Để bám được theo quỹ đạo, các kỹ thuật sử dụng logíc mờ với thông tin đầu vào từ hệ thống xử lý ảnh đã được nghiên cứu và áp dụng. Phương pháp điều khiển sử dụng trong hệ thống là sự kết hợp giữa bộ điều khiển lái -bộ điều khiển lai PID-mờ, và bộ điều khiển vận tốc tuyến tính -bộ điều khiển mờ. Để khẳng định tính đúng đắn của giải thuật điều khiển, chúng tôi đã tiến hành thử nghiệm trên một robốt tự hành, robốt thiết kế dựa trên cơ sở các linh kiện sẵn có trên thị trường. Thử nghiệm chỉ ra rằng, robốt sử dụng giải thuật chúng tôi đề xuất bám tốt theo quỹ đạo cho trước -bao gồm cả quỹ đạo cong và quỹ đạo thẳng. Từ khóa: Hệ thống điều khiển, robốt tự hành, hệ thống xử lý ảnh, logíc mờ, bộ điều khiển lái, bộ điều khiển tốc độ. AbstractIn this work, we propose a method for autonomous path/line following of differential-drive wheeled robot to track straight and curved paths in an indoor environment. In order to follow the path/line, fuzzy logic techniques are applied to generate movement with the information extracted from vision system. The control method in the system combines a steering controller, which is implemented by an intelligent hybrid fuzzy PID controller, controlling the steering angle of the robot, and fuzzy velocity controller, which controls the forward linear velocity with the purpose of safe tracking. We do experiments using an open source differential-drive wheeled robot platform (Figure 1). In the experiments, the robot is successfully able to follow a pre-defined path/line containing both straight and curved sections. The effectiveness of the control algorithm, combining steering and velocity controllers, is examined in these experiments. Keywords: Control systems, vision system, fuzzy logic, steering controller, velocity controller. List of Symbols

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“…In terms of the path planning in completely unknown environment, common methods includes: Artificial potential field method [2][3][4], fuzzy logic algorithm [5,6], and the Bug approach. Lumelsk, Mukhopadhyay, et al proposed the Bug [7,8] and the VisBug [9] algorithm.…”

Section: Introductionmentioning

confidence: 99%

RandomBug: Novel Path Planning Algorithm in Unknown Environment

Xu¹

2014

TOEEJ

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This paper presents a novel real-time path planning algorithm for an autonomous mobile agent in completely unknown environment. In this algorithm, all the planned paths are described and stored in the form of vectors in the algorithm. Only the rotation angle and the movement distance in a single direction are considered when the autonomous moves along the planned paths. The algorithm combines range sensor data with a safety radius, which determines the blocking obstacles and calculates a shorter path by choosing the random intermediate points. These random intermediate points are be generated when blocking obstacles exist in the current path. Then the optimal intermediate points are selected and inserted into the current path to regenerate a new planned path. Simulation results are shown that the proposed algorithm is effective.

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A Fuzzy-Logic-Based Approach for Mobile Robot Path Tracking

Cited by 205 publications

References 29 publications

Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review

Mobile Robot Navigation and Obstacle Avoidance Techniques: A Review

Vision Based Autonomous Path/Line Following of a Mobile Robot Using a Hybrid Fuzzy PID Controller

RandomBug: Novel Path Planning Algorithm in Unknown Environment

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