RRT Path Planning and Morphological Segmentation Based Navigation for a Tetrapod Robot

Aguilar, Wilbert G.; Caballeros, Jessica; Segarra, David; Castro, Patricio

doi:10.1007/978-3-030-02849-7_25

Cited by 1 publication

(1 citation statement)

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“…It then connects existing nodes that are closer to each sample, ultimately creating an optimal route map from the starting point to the target. [ 149 ] Aguilar et al [ 150 ] based on the RRT method, determined the path between the initial position and the final position in the detected obstacle environment through morphological segmentation, thereby achieving autonomous motion of a spider robot. However, the path generated by the RRT algorithm may lack smoothness, leading to increased convergence time in environments with narrow passages or numerous obstacles.…”

Section: Autonomous Motionmentioning

confidence: 99%

A Review of Quadruped Robots: Structure, Control, and Autonomous Motion

Fan,

Pei,

Wang

et al. 2024

Advanced Intelligent Systems

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With their unique point‐contact ability with the ground and exceptional adaptability to complex terrains, quadruped robots have become a focal point in the fields of automation and robotic engineering. Significant research progress has been made in aspects such as structural design, motion planning, and balance control of these robots. However, a primary challenge in current research lies in further enhancing the dynamic performance, environmental adaptability, and payload capacity. In this article, research achievements in key technical areas of quadruped robots, encompassing structural design, gait planning, traditional control strategies, intelligent control strategies, and autonomous movement, are comprehensively discussed. The focus of the article is on analyzing trends in intelligence and technological innovation within the aforementioned areas, aiming to provide robust theoretical support and forward‐looking technical guidance for quadruped robots research. Additionally, it offers valuable references for scholars engaged in this field.

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Section: Autonomous Motionmentioning

confidence: 99%