Aug 2026· SLAS technology· pp.
100463
· 0 citations· 33 references
Medicine
Abstract
The emergence of autonomous laboratories is accelerating discovery in chemistry, drug discovery, materials science, and related fields by enabling high-throughput, data-driven experimentation. However, the integration of heterogeneous robotic systems, ranging from fixed manipulators to mobile platforms, introduces safety challenges that are not systematically addressed in newly established laboratories. In this context, this work aims to raise awareness of robotic safety among chemists and biologists leading laboratory automation projects who may have limited access to industrial robotics expertise. To support a preliminary evaluation of existing or newly developed automated laboratory systems, we explain and demonstrate the use of a simple, structured safety assessment methodology based on ISO standards and tailored to laboratory environments. The framework combines established robotics safety standards with laboratory-specific considerations, including chemical hazards, human-robot interaction, and dynamic workflows. To facilitate its adoption by scientists, the methodology is illustrated through a case study conducted at the Swiss CAT+ West Hub autonomous laboratory, focusing on a multi-instrument analytical platform integrating collaborative robotic arms and mobile robotic systems. The proposed framework follows a six-step iterative process encompassing system definition, hazard identification, risk estimation, risk reduction, and validation. Its applicability was evaluated through the case study, in which sixteen hazards were identified, with robot-human collisions and chemical exposure representing the most critical risks. Experimental force and pressure measurements further demonstrated that widely used collaborative robots may exceed accepted safety thresholds under realistic operating conditions, particularly as a consequence of end-effector design and task-dependent motion characteristics. Risk mitigation strategies based on dynamic safety zoning, sensor-based human detection, and operational mode control were implemented to ensure compliance with safety requirements. The results highlight the need for systematic, context-specific safety assessments in autonomous laboratories and demonstrate that collaborative robots are not inherently safe without rigorous validation. This work provides a practical framework for the safe deployment of robotic systems in autonomous and digital laboratory environments.
Industrial robots underlie modern manufacturing automation, yet conventional deterministic control based on fixed trajectories and offline programming struggles under high-mix and flexible production. Embodied artificial intelligence (EAI) offers a promising alternative by coupling perception, reasoning, and action within closed-loop physical interaction, enabling industrial robots to adapt behaviors online rather than execute predefined tasks. Yet, general-purpose EAI remains difficult to deploy in industrial environments due to stringent requirements on precision, real-time performance, reliability, and safety. These challenges have motivated increasing interest in embodied artificial intelligence for industry (EAI4I). This paper presents a systematic survey of EAI4I from an industrial robotics perspective. Specifically, we first analyze the quantified requirements of industrial robots enabled by EAI4I. Afterwards, recent research progress is reviewed, covering core technologies for single- and multi-robot systems, dedicated hardware platforms, high-fidelity simulators, task-specific datasets, representative industrial application scenarios, and critical deployment challenges. Finally, promising directions toward EAI4I are discussed.
Haibin Yu, Chunhe Song, Yinlong Zhang et al.· National Science Review· 0 citations
Robots are being deployed for an increasingly diverse set of purposes, from industrial manufacturing to delivery, inspection, and surgical assistance, and the systems entering these roles are markedly more capable than earlier generations, utilizing learned perception, language-based planning, and multi-sensor input. This increase in the number of deployments is reflected in industry forecasts that report rapid, sustained growth in industrial robot installations and in the worldwide operational stock [18]. As robots take on broader and more complex missions in human-centered environments, their quality assurance and physical safety become increasingly relevant. However, despite this growth and advancements, few existing works offer a comprehensive review of robotic test automation with its conventional, AI-powered, and agentic landscape and overall trends. This paper addresses this gap by summarizing, classifying, and visualizing conventional and AI-based robot testing. Extending this, a reading of the commercial landscape suggests that conventional and AI methods act as complements rather than substitutes. Lastly, this work portrays many problems, challenges, and needs to aid in future research.
Karthik Rengarajan, Siddharth Pokuri, J. Gao· International Conference on...· 0 citations
Research and current innovations required more open-source tools to enhance the multidisciplinary kind of research growth. Thus, open-source tools are very fruitful specially in case of robotics and automation systems. Because of this any user can design and test virtually before wasting the time and money to implement a physical model. In this research paper major focus is to develop a prototype model using open-source resources. It’s required since robotics and automation have significantly transformed human society, beginning with the industrial revolution when machinery revolutionized labor set the foundation for modern industry. The primary reason of the fast growth of automation is evolving rapidly through advancements in artificial intelligence (AI), which allows machines to do complex tasks. In the coming years, this new wave of automation is expected to drive substantial change, improving productivity and accuracy across industry. So, through this research work an attempt has been tried to explores the role of robotics and automation in both historical and modern context, examining their potential to shape a more efficient future while considering the societal impact using different open-source tools and latest technologies. It also addresses future challenges, including the need for ethical framework, cybersecurity safeguard, and workforce reskilling initiatives. The major tools are used here is Arduino IDE, Tinker cad, coppelia-Sim, Circuit verse etc. Addressing these issues proactively will be crucial to ensuring that robotic and automation continue to benefit society equitably.
Priyanka Mishra, Upkar Singh Kandhari, Anchana B S et al.· 2026 4th International Confe...· 0 citations
Pipeline robots represent intelligent systems engineered for confined and complex pipeline environments. They feature compact and flexible architectures, diverse locomotion modalities, and a high degree of functional integration. These systems have been widely applied in industrial equipment inspection, energy infrastructure maintenance, and the management of urban underground utilities. This review systematically analyzes the technological characteristics and recent advancements in pipeline robotics, with a focus on drive mechanisms and motion control strategies. It presents the evolution and comparative analysis of three primary drive architectures: passive-driven, self-driven, and compound-driven, with representative applications, advantages, and limitations. In addition, an integrated research framework is proposed that encompasses energy efficiency management, drive systems, adaptive mechanisms, perception, navigation, and intelligent adaptive control to address critical challenges in environmental adaptability, energy efficiency, and autonomous task execution. Finally, the review outlines emerging trends and unresolved technical bottlenecks, providing theoretical insights and practical guidance to support ongoing innovation and real-world deployment of pipeline robotic systems.
Cheng Liu, Ke Niu, Chengrong Kuang et al.· Robotica (Cambridge. Print)· 0 citations
Robotic arms, as core executive components of industrial automation and intelligent robotics, are widely applied in industrial manufacturing, agricultural picking, medical rehabilitation, aerospace, and other fields. This paper systematically reviews the development history and current research status of robotic arms, focusing on structural design innovations, including rigid -flexible switching, bionic configurations, and lightweight materials, as well as intelligent control technologies, such as adaptive c ontrol, machine vision fusion, and human-machine interaction. The key technical bottlenecks that restrict the development of robotic arms are analyzed, including the trade -off between lightweight design and high load capacity, accuracy errors due to flexible deformation, poor adaptability in unstructured environments, and high operational costs. Finally, the future development trends of robotic arms are predicted to center on bionic integration, intelligent collaboration, modular customization, and green, energy-saving technologies, thereby providing a theoretical reference and technical support for subsequent research and engineering applications.
The evolution of SDLs is charts their evolution from bespoke systems to interoperable platforms, highlighting challenges in scalability, generalizability and data provenance, and outlining pathways towards networked, trustworthy infrastructures enabling collective scientific superintelligence.
Richard B. Canty, M. Abolhasani· Nature Reviews Chemistry· 0 citations