Recent Advances and Challenges in Industrial Robotics: A Systematic Review of Technological Trends and Emerging Applications

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