Robot path planning usingwavefront approach with wall-following

Amir, Muhammad; Iraji, R.

doi:10.1109/iccsit.2009.5234918

Cited by 6 publications

(4 citation statements)

References 5 publications

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“…When a cell is not an obstacle and not assigned a given value yet, it will be assigned with a value. The value of each cell of grid map will be measured based on this formula [2]:…”

Section: Wavefront Algorithm and Modified Wavefront Algorithmmentioning

confidence: 99%

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Comparison between Normal Waveform and Modified Wavefront Path Planning Algorithm for Mobile Robot

Tang

Yeong²,

Su³

2014

AMM

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Mobile robot path planning is about finding a movement from one position to another without collision. The wavefront is typically used for path planning jobs and appreciated for its efficiency, but it needs full wave expansion which takes significant amount of time and process in large scale environment. This study compared wavefront algorithm and modified wavefront algorithm for mobile robots to move efficiently in a collision free grid based static environment. The algorithms are compared in regards to parameters such as execution time of the algorithm and planned path length which is carried out using Player/Stage simulation software. Results revealed that modified wavefront algorithm is a much better path planning algorithm compared to normal wavefront algorithm in static environment.

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“…When a cell is not an obstacle and not assigned a given value yet, it will be assigned with a value. The value of each cell of grid map will be measured based on this formula [2]:…”

Section: Wavefront Algorithm and Modified Wavefront Algorithmmentioning

confidence: 99%

“…The problem of path planning has been an extremely active area of study. There are numerous algorithms of robot path planning in static and dynamic environments [1] such as A*, artificial potential field and wave expansion also several methods exist for enhancing performance and increasing execution speed [2].…”

Section: Introductionmentioning

confidence: 99%

Comparison between Normal Waveform and Modified Wavefront Path Planning Algorithm for Mobile Robot

Tang

Yeong²,

Su³

2014

AMM

View full text Add to dashboard Cite

show abstract

“…When a cell is not an obstacle and not assigned a given value yet, it will be assigned with a value. The value of each cell of grid map will be measured based on this formula [3]:…”

Section: Wavefront Algorithmmentioning

confidence: 99%

Comparison between Waveform and Bug Path Planning Algorithm for Mobile Robot

Tang

Yeong²,

Su³

2014

AMM

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Mobile robots frequently find themselves in a circumstance where they need to find a trajectory to another position in their environment, subject to constraints postured by obstacles and the capabilities of the robot itself. This study compared path planning algorithms for mobile robots to move efficiently in a collision free grid based static environment. Two algorithms have been selected to do the comparison namely wavefront algorithm and bug algorithm. The wavefront algorithm involves a breadth-first search of the graph beginning at the goal position until it reaches the start position. The bug algorithm uses obstacles borders as guidance toward a goal with restricted details about the environment. The algorithms are compared in terms of parameters such as execution time of the algorithm and planned path length by using Player/Stage simulation software. Results shown that wavefront algorithm is a better path planning algorithm compared to bug algorithm in static environment.

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“…However, the local minima problem exists and may prevent the robot from real-time stable and smooth avoidance of the obstacle. Traditional strategies such as wall-following and modified APF methods may not solve this problem fast [1,11,12]. In addition, the size of the robot is not considered in these methods, which may lead to unfeasible paths and brings negative effects for global optimal path planning.…”

Section: Introductionmentioning

confidence: 99%

Obstacle avoidance for mobile robot based on improved dynamic window approach

Liu¹,

Liu²,

Liu³

et al. 2017

Turk J Elec Eng & Comp Sci

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Abstract:The dynamic window approach has the drawback that it may result in local minima and nonoptimal motion decision for obstacle avoidance because of not considering the size constraint of a mobile robot. Thus, an improved dynamic window approach is proposed, which takes into account the relation between the size of the mobile robot and the free space between obstacles. A laser range finder is employed to improve the ability of sensing and prediction of the environment, in order to avoid being trapped in a U-shaped obstacle, such as a box canyon. By applying the proposed method, the local minima problem can be solved and the optimal path can be obtained. The effectiveness and superiority is proven by theoretic analysis and simulations.

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Robot path planning usingwavefront approach with wall-following

Cited by 6 publications

References 5 publications

Comparison between Normal Waveform and Modified Wavefront Path Planning Algorithm for Mobile Robot

Comparison between Normal Waveform and Modified Wavefront Path Planning Algorithm for Mobile Robot

Comparison between Waveform and Bug Path Planning Algorithm for Mobile Robot

Obstacle avoidance for mobile robot based on improved dynamic window approach

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