Faster Implementation of The Dynamic Window Approach Based on Non-Discrete Path Representation

Lin, Ziang; Taguchi, Ryo

doi:10.3390/math11214424

Cited by 1 publication

(2 citation statements)

References 33 publications

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“…At the beginning of this flow, it samples all the speed pairs corresponding to the kinematic constraints of the robot. DWA computes the coordinates of the waypoints for each input velocity pair using iterations ( 23 ) to ( 25 ) [ 168 ].

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Section: Heuristic Approachmentioning

confidence: 99%

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Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Katona,

Neamah,

Korondi

2024

Sensors

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Path planning creates the shortest path from the source to the destination based on sensory information obtained from the environment. Within path planning, obstacle avoidance is a crucial task in robotics, as the autonomous operation of robots needs to reach their destination without collisions. Obstacle avoidance algorithms play a key role in robotics and autonomous vehicles. These algorithms enable robots to navigate their environment efficiently, minimizing the risk of collisions and safely avoiding obstacles. This article provides an overview of key obstacle avoidance algorithms, including classic techniques such as the Bug algorithm and Dijkstra’s algorithm, and newer developments like genetic algorithms and approaches based on neural networks. It analyzes in detail the advantages, limitations, and application areas of these algorithms and highlights current research directions in obstacle avoidance robotics. This article aims to provide comprehensive insight into the current state and prospects of obstacle avoidance algorithms in robotics applications. It also mentions the use of predictive methods and deep learning strategies.

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Section: Heuristic Approachmentioning

confidence: 99%

“…After assessing all possible speed pairs, the optimal speed command is generated. This model is extensively utilized in research involving wheeled robots [ 168 ].…”

Section: Heuristic Approachmentioning

confidence: 99%