Generalized Voronoi Diagram-Guided and Contact-Optimized Motion Planning for Snake Robots

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F26%3A0200875" target="_blank" >RIV/00216305:26210/26:0200875 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/2227-7390/14/2/332" target="_blank" >https://www.mdpi.com/2227-7390/14/2/332</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/math14020332" target="_blank" >10.3390/math14020332</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Generalized Voronoi Diagram-Guided and Contact-Optimized Motion Planning for Snake Robots

Popis výsledku v původním jazyce

In robot motion planning in a space with obstacles, the goal is to find a collision-free path for robots from the start to the target position. Numerous fundamentally different approaches, and their many variants, address this problem depending on the types of obstacles, the dimensionality of the space and the restrictions on robot movements. We present a hierarchical motion planning framework for snake-like robots navigating cluttered environments. At the global level, a bounded Generalized Voronoi Diagram (GVD) generates a maximal-clearance path through complex terrain. To overcome the limitations of pure avoidance strategies, we incorporate a local trajectory optimization layer that enables Obstacle-Aided Locomotion (OAL). This is realized through a simulation-in-theloop system in CoppeliaSim, where gait parameters are optimized using Particle Swarm Optimization (PSO) based on contact forces and energy efficiency. By coupling high-level deliberative planning with low-level contact-aware control, our approach enhances both adaptability and locomotion efficiency. Experimental results demonstrate improved motion performance compared to conventional planners that neglect environmental contact.

Název v anglickém jazyce

Generalized Voronoi Diagram-Guided and Contact-Optimized Motion Planning for Snake Robots

Popis výsledku anglicky

In robot motion planning in a space with obstacles, the goal is to find a collision-free path for robots from the start to the target position. Numerous fundamentally different approaches, and their many variants, address this problem depending on the types of obstacles, the dimensionality of the space and the restrictions on robot movements. We present a hierarchical motion planning framework for snake-like robots navigating cluttered environments. At the global level, a bounded Generalized Voronoi Diagram (GVD) generates a maximal-clearance path through complex terrain. To overcome the limitations of pure avoidance strategies, we incorporate a local trajectory optimization layer that enables Obstacle-Aided Locomotion (OAL). This is realized through a simulation-in-theloop system in CoppeliaSim, where gait parameters are optimized using Particle Swarm Optimization (PSO) based on contact forces and energy efficiency. By coupling high-level deliberative planning with low-level contact-aware control, our approach enhances both adaptability and locomotion efficiency. Experimental results demonstrate improved motion performance compared to conventional planners that neglect environmental contact.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2026

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Mathematics

ISSN

—

e-ISSN

2227-7390

Svazek periodika

14

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

17

Strana od-do

1-17

Kód UT WoS článku

001670988100001

EID výsledku v databázi Scopus

2-s2.0-105028598699