Obstacle avoidance for mobile robot based on improved dynamic window approach

Liu, Xiuyun; Liu, Fei; Liu, Juan; Shan, Liang

doi:10.3906/elk-1504-194

Cited by 31 publications

(24 citation statements)

References 17 publications

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“…DWA also has the drawback of resulting in local minima problems and nonoptimal motion decision due to constraints of the mobile robot the approach could not manage [75,[102][103][104].…”

Section: Challenges Of Conventional Path Planning Methodsmentioning

confidence: 99%

“…Some researchers also considered the dynamic window approach (DWA) to provide optimal obstacle avoidance [70][71][72][73][74]. Recently, an improved dynamic window approach was proposed in [75] for mobile robot obstacle avoidance. Considering the drawbacks of local minima of this approach causing the robot to be trapped in a U-shaped obstacle, a laser range finder was used as the sensor to ensure optima path decision making of the robot.…”

Section: Dynamic Window Path Planningmentioning

confidence: 99%

See 1 more Smart Citation

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

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Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles. There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems. This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem. The main strengths and challenges of path planning methods employed by researchers were identified and discussed. Future directions for path planning research is given. The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.

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“…DWA also has the drawback of resulting in local minima problems and nonoptimal motion decision due to constraints of the mobile robot the approach could not manage [75,[102][103][104].…”

Section: Challenges Of Conventional Path Planning Methodsmentioning

confidence: 99%

Section: Dynamic Window Path Planningmentioning

confidence: 99%

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…As a result, it is more desirable than the VPH and VFH+ [ 9 ]. The DWA method has also been widely used since high-speed navigation can be obtained [ 10 ]. The improved DWA method, known as I-DWA, has been proposed, and applied to computing in real-time autonomous robot navigation [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

“…In order to cope with a sudden situation, input commands for collision avoidance should be generated in real time, based on information about the surrounding environment such as map and sensor data [ 13 , 14 ]. Conventional obstacle avoidance methods have been proposed to avoid obstacles in such a way that bypasses and maintains a certain distance from the closest and most interesting obstacles based on sensor data [ 1 , 2 , 10 ]. These methods generally show good performance, but often show incomplete performance in terms of navigation in specific environments such as doors, narrow corridors, etc.…”

Section: Introductionmentioning

confidence: 99%

Range Sensor-Based Efficient Obstacle Avoidance through Selective Decision-Making

Shim

Kim

2018

Sensors

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In this paper, we address a collision avoidance method for mobile robots. Many conventional obstacle avoidance methods have been focused solely on avoiding obstacles. However, this can cause instability when passing through a narrow passage, and can also generate zig-zag motions. We define two strategies for obstacle avoidance, known as Entry mode and Bypass mode. Entry mode is a pattern for passing through the gap between obstacles, while Bypass mode is a pattern for making a detour around obstacles safely. With these two modes, we propose an efficient obstacle avoidance method based on the Expanded Guide Circle (EGC) method with selective decision-making. The simulation and experiment results show the validity of the proposed method.

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“…Infrared range sensors data applying to the fuzzy logic control inputs, this data has been used to avoid the obstacle when moving the robot from a starting point to a destination point [14] on a map. Additionally, Robot control and navigation applications have been implemented using different algorithms and methods [15]- [17] [18], [19]. Webots simulator is developed for the robots which are a development environment used to model, program and simulate mobile robots.…”

Section: Related Workmentioning

confidence: 99%

Collision-Free Mobile Robot navigation using Fuzzy Logic Approach

Dirik¹

2018

IJCA

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Autonomous mobile robots' navigation has become a very popular and interesting topic of computer science and robotics in the last decade. Many algorithms have been developed for robot motion control in an unknown (indoor/outdoor) and in various environments (static/dynamic). Fuzzy logic control techniques are an important algorithm developed for robot navigation problems. The aim of this research is to design and develop a fuzzy logic controller that enables the mobile robot to navigate to a target in an unknown environment, using WEBOTS commercial mobile robot simulation and MATLAB software. The algorithm is divided into two stages; In the first stage, the mobile robot was made to go to the goal, and in the second stage, obstacle avoidance was realized. Robot position information (x, y, Ø) was used to move the robot to the target and six sensors data were used during the obstacle avoidance phase. The used mobile robot (E_PUCK) is equipped with 12 IR sensors to measure the distance to the obstacles. The fuzzy control system is composed of six inputs grouped in doubles which are left, front and right distance sensors two outputs which are the mobile robot's left and right wheel speeds. To check the simulation result for proposed methodology, WEBOTS simulator and MATLAB software were used. To modeling the environment in different complexity and design, this simulator was used. The experimental results have shown that the proposed architecture provides an efficient and flexible solution for autonomous mobile robots and the objective of this research has been successfully achieved. This research also indicated that WEBOT and MATLAB are suitable tools that could be used to develop and simulate mobile robot navigation system.

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Obstacle avoidance for mobile robot based on improved dynamic window approach

Cited by 31 publications

References 17 publications

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Range Sensor-Based Efficient Obstacle Avoidance through Selective Decision-Making

Collision-Free Mobile Robot navigation using Fuzzy Logic Approach

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