English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this article, we propose a new method for constraints evaluation during the path planning of a multi-legged walking robot. We propose the application of Gaussian Mixtures (GM) to build constraint models. With the proposed analytical constraint function we can compute the gradient and move the robot out of the bound configuration. The proposed method allows checking self-collisions, and a workspace of the robot in a few microseconds and efficiently plan the motion of the robot. The proposed path planning method uses RRT-Connect framework. We show how to efficiently apply the constraints evaluation methods to optimize the posture of the robot, optimize the position of the feet during the swing phase and efficiently explore the search space. We compare the proposed method with the standard constraints evaluation algorithms. Finally, we present the results of path planning for the six-legged robot in various scenarios to show properties of the proposed motion planning algorithm with GM-based constraints evaluation.

Efficient Modeling and Evaluation of Constraints in Path Planning for Multi-Legged Walking Robots