Processes, Journal Year: 2025, Volume and Issue: 13(3), P. 832 - 832
Published: March 12, 2025
Industrial robotics has shifted from rigid, task-specific tools to adaptive, intelligent systems powered by artificial intelligence (AI), machine learning (ML), and sensor integration, revolutionizing efficiency human–robot collaboration across manufacturing, healthcare, logistics, agriculture. Collaborative robots (cobots) slash assembly times 30% boost quality 15%, while reinforcement enhances autonomy, cutting errors energy use 20%. Yet, this review transcends descriptive summaries, critically synthesizing these trends expose unresolved tensions in scalability, cost, societal impact. High implementation costs legacy system incompatibilities hinder adoption, particularly for SMEs, interoperability gaps—despite frameworks, like OPC UA—stifle multi-vendor ecosystems. Ethical challenges, including workforce displacement cybersecurity risks, further complicate progress, underscoring a fragmented field where innovation outpaces practical integration. Drawing on systematic of high-impact literature, study uniquely bridges technological advancements with interdisciplinary applications, revealing disparities economic feasibility equitable access. It critiques the literature’s isolation trends—cobots’ safety, ML’s perception’s precision—proposing following cohesive research directions: cost-effective modularity, standardized protocols, ethical frameworks. By prioritizing interoperability, sustainability, paper charts path evolve inclusively, offering actionable insights researchers, practitioners, policymakers navigating dynamic landscape.
Language: Английский