Szczegóły publikacji
Opis bibliograficzny
Analysis of the CPG-DRL framework for quadruped robot locomotion / Ravi Raj, Andrzej KOS // International Journal of Electronics and Telecommunications ; ISSN 2081-8491 . — Tytuł poprz.: Kwartalnik Elektroniki i Telekomunikacji = Electronics and Telecommunications Quarterly. — 2026 — vol. 72 no. 2, s. 1–7. — Bibliogr. s. 7, Abstr. — Publikacja dostępna online od: 2026-05-16
Autorzy (2)
- Raj Ravi
- AGHKos Andrzej
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 167969 |
|---|---|
| Data dodania do BaDAP | 2026-06-16 |
| Tekst źródłowy | URL |
| DOI | 10.24425/ijet.2026.157906 |
| Rok publikacji | 2026 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | International Journal of Electronics and Telecommunications |
Abstract
Autonomous robots are expected to be crucial in mitigating the lack of precise border surveillance in complex terrains, especially within forests, mountains, and industrial settings, focused on predicting the entry of terrorists and illegal refugees. These robots must demonstrate navigational proficiency in both controlled areas, such as border control gates and borders with plane surfaces, and unplanned country borders in daily surveillance tasks, including mountains, forests, and mud. In this regard, quadruped robots are attracting considerable interest due to their ability to carry substantial surveillance equipment while navigating inclines and obstacles. Given the environment-dependent characteristics of optimal gait patterns, it becomes a necessity for mechanisms capable of independently and effectively optimizing gait patterns for adaptation to different scenarios. To address these challenges, we explored a model for quadruped locomotion that combines central pattern generators (CPGs) with deep reinforcement learning (DRL). Using both external and internal sensing, the agent learns to coordinate rhythmic movement among multiple oscillators to follow speed instructions, while also adjusting these instructions to avoid bumping into things around it. This research helps to use DRL to study important questions in neurology, such as how certain pathways, connections between oscillators, and sensory information affect walking patterns. Moreover, this paper will present fundamental knowledge, research trends, and challenges regarding the implementation of the CPG-DRL framework in robotic perception.
