Robotics and automation is the interdisciplinary field concerned with designing, building, and programming machines that can sense their environment, make decisions, and perform physical tasks with reduced or no human intervention. It draws on mechanical and electrical engineering for actuators and sensors, control theory for motion planning and stability, and artificial intelligence for perception, decision-making, and adaptive behavior. Key research areas include simultaneous localization and mapping for navigation, computer vision for object recognition and manipulation, human-robot interaction, swarm robotics, and reinforcement learning for control policies. Adoption of vision-language-action models in robotics reportedly tripled between 2025 and 2026 and is now present in roughly 40 percent of new robot deployments, reflecting rapid progress in perception and control research. Applications span industrial automation and manufacturing, autonomous vehicles and drones, agricultural robotics, warehouse logistics, and assistive and surgical robotics in healthcare. As an open-access robotics journal, IJACSA covers robotics and automation research spanning control algorithms, perception systems, and applied automation across industrial and service domains.
Published in International Journal of Advanced Computer Science and Applications (IJACSA)
· list last refreshed October 2026
Automotive seat cover assembly entails the manual collection of plastic J-shaped clips from boxes located at a non-ergonomic distance from the sewing stations. Operators are compelled to inadvertently pick up multiple co…
This study examines the adoption of digital technologies and artificial intelligence (AI) in Slovak firms, with particular attention to technological integration, employee adaptation, and organizational change. The study…
Television companies face significant problems in managing advertising orders due to manual processes that cause transcription errors, delays, and a lack of traceability. This study proposes a web application based on cl…
Large Language Models (LLMs) that are enhanced with Retrieval-Augmented Generation(RAG) can aid in internal auditing, particularly in search and analysis of documents. However, in general, most RAG-based audit tools focu…
This study proposes a hybrid modeling and control framework for intelligent wheelchair systems that integrates formal methods with adaptive artificial intelligence to ensure safety, robustness, and real-time performance.…
Global crises, such as pandemics and climate-related disasters, place unprecedented strain on healthcare Systems, exposing weaknesses in resource management and patient care. This study aims to address these challenges b…
This study presents the design, development, and evaluation of an intelligent fruit-picking robot that integrates convolutional vision, adaptive gripping mechanisms, and kinematic control to enable automated harvesting i…
The rapid expansion of Business Process Outsourcing (BPO) has transformed the global services economy, and Albania is emerging as a competitive nearshoring destination in the Western Balkans. This study examines the inte…
Manual test case generation for agile software development is a critical bottleneck that is costly, inconsistent, and error-prone. This study introduces a prompt-engineering and multi-level orchestration framework to aut…
This paper presents a comprehensive Model-Driven Engineering (MDE) methodology for automatically transforming Business Process Model and Notation (BPMN) diagrams into executable blockchain-based smart contracts. The prop…