Title: Unifying advanced meta-systems for AI-driven bipedal robot locomotion

Authors: R. Sivakani; M. Mahasree; K.N. Sunil Kumar; Puneet Mittal; S. Chitra Selvi; Sukhwinder Singh Sran

Addresses: Department of Artificial Intelligence and Data Science, Dhaanish Ahmed College of Engineering, Chennai, 601301, Tamil Nadu, India ' Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, 600089, Tamil Nadu, India ' Department of Computer Science and Engineering- Cyber Security, Sri Venkateshwara College of Engineering, Bengaluru, 562157, Karnataka, India ' Department of Artificial Intelligence and Machine Learning, Manipal University Jaipur, Jaipur, 303007, Rajasthan, India ' Department of Electrical and Electronics Engineering, University College of Engineering – Dindigul, (A constituent college of Anna University – Chennai), Dindigul , 624 612, Tamil Nadu, India ' Department of Computer Science and Engineering, Punjabi University, Patiala, 147002, Punjab, India

Abstract: Digitisation has made complicated meta-system integration essential. This paper examines the confluence of artificial intelligence (AI) and robotics, which combine computer science, mechanical engineering, and electronics engineering. Here, we design and test a two-legged, self-adaptive mobile robot. This robot replicates human activities and learns from its environment, creating a humanoid meta-system. The study employs advanced machine learning algorithms, namely, Naïve Bayes and support vector machines (SVM), to analyse and classify the medium of locomotion for the robot. Our approach adopts a data split ratio of 80 : 20 for training and testing, respectively. We use 10-fold cross-validation to test our models' robustness using precision, recall, and accuracy. Our findings indicate that the SVM model outperforms, with metrics scoring 84%, 85%, and 88%, respectively, demonstrating the effectiveness of integrating complex meta-systems in enhancing robotic capabilities. This updated study contains the original research but emphasises complicated system integration, making it more relevant and accessible to a larger audience, including Polytron's potential clients interested in cutting-edge digital solutions.

Keywords: mobile robot; locomotion; humanoid; Naïve Bayes; SVM; support vector machine; modelling adaptive control; bipedal robots; A single inflexible body; artificial intelligence; kinematic modelling; digital actuator.

DOI: 10.1504/IJSSE.2026.154878

International Journal of System of Systems Engineering, 2026 Vol.16 No.3, pp.309 - 335

Received: 27 Oct 2023
Accepted: 01 Feb 2024
Published online: 17 Jul 2026 *

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