Robotic Process Automation (RPA) is a fast-emerging automation technology that sits between the fields of Business Process Management (BPM) and Artificial Intelligence (AI), and allows organizations to automate high volume routines. RPA tools are able to capture the execution of such routines previously performed by a human users on the interface of a computer system, and then emulate their enactment in place of the user by means of a software robot. Nowadays, in the BPM domain, only simple, predictable business processes involving routine work can be automated by RPA tools in situations where there is no room for interpretation, while more sophisticated work is still left to human experts. In this paper, starting from an in-depth experimentation of the RPA tools available on the market, we provide a classification framework to categorize them on the basis of some key dimensions. Then, based on this analysis, we derive four research challenges and discuss prospective approaches necessary to inject intelligence into current RPA technology, in order to achieve more widespread adoption of RPA in the BPM domain.
Intelligent Automation for Embodied Benchmark Construction: Pipelines, Embodiments, Simulators, and Trends
University of Electronic Science and Technology of China（电子科技大学）；Qiyuan Lab（启元实验室）；Beijing University of Posts and Telecommunications（北京邮电大学）；Tsinghua University（清华大学）；Beihang University（北京航空航天大学）
Robust Quantum Controllers: Quantum Information -- Thermodynamic Hidden Force Control in Intelligent Robotics based on Quantum Soft Computing
Institute of System Analysis and Management, Dubna State University（杜布纳国立大学系统分析与管理研究所）；Joint Institute for Nuclear Research (JINR)（联合核子研究所）；Moscow State University of Geodesy and Cartography (MIIGAiK)（莫斯科测绘大学）；Yamaha Motor Co. Ltd.（雅马哈发动机株式会社）
NIMS-OS: An automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science
Center for Basic Research on Materials（材料基础研究中心）；National Institute for Materials Science（国家材料科学研究所）；Graduate School of Frontier Sciences, The University of Tokyo（东京大学前沿科学研究生院）；Research Center for Energy and Environmental Materials(GREEN)（能源与环境材料研究中心（GREEN））；Center for Advanced Battery Collaboration, Research Center for Energy and Environmental Materials (GREEN)（先进电池协作中心，能源与环境材料研究中心（GREEN））
Unconventional Cognitive Intelligent Robotic Control: Quantum Soft Computing Approach in Human Being Emotion Estimation -- QCOptKB Toolkit Application
Institute of System Analysis and Management, Dubna State University（杜布纳国立大学系统分析与管理研究所）；Joint Institute for Nuclear Research (JINR)（联合核研究所）；Moscow State University of Geodesy and Cartography (MIIGAiK)（莫斯科测绘与制图大学）；Yamaha Motor Co. Ltd.（雅马哈发动机株式会社）
Holistic Construction Automation with Modular Robots: From High-Level Task Specification to Execution
Technical University of Munich, Department of Computer Engineering（慕尼黑技术大学计算机工程系）；Munich Center for Machine Learning (MCML)（慕尼黑机器学习中心）；Fraunhofer Italia Research, Robotics and Intelligent Systems Engineering（弗劳恩霍夫意大利研究所机器人与智能系统工程）
RoCo Challenge at AAAI 2026: Benchmarking Robotic Collaborative Manipulation for Assembly Towards Industrial Automation
Nanyang Technological University, Singapore（南洋理工大学，新加坡）；Beijing University of Posts and Telecommunications, Beijing, China（北京邮电大学，北京，中国）；Carnegie Mellon University, Pittsburgh, USA（卡内基梅隆大学，匹兹堡，美国）；Agency for Science, Technology and Research (A*STAR), Singapore（科技研究局（A*STAR），新加坡）
ProAgent: From Robotic Process Automation to Agentic Process Automation
Tsinghua University（清华大学）；Massachusetts Institute of Technology（麻省理工学院）；Carnegie Mellon University（卡内基梅隆大学）；ModelBest Inc.（ModelBest公司）；Renmin University of China（中国人民大学）
Intelligent Approval of Access Control Flow in Office Automation Systems via Relational Modeling
College of Computer Science and Software Engineering, Shenzhen University（深圳大学计算机与软件学院）；Alibaba Group Holding Limited（阿里巴巴集团控股有限公司）；Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)（广东省人工智能与数字经济实验室（深圳））；Cyberspace Institute of Advanced Technology, Guangzhou University（广州大学网络空间先进技术研究院）；Shenzhen Technology University（深圳技术大学）
Intelligent methods for business rule processing: State-of-the-art
Universidade do Vale do Rio dos Sinos - UNISINOS（南里约 dos Sinos大学（UNISINOS））；Software Innovation Laboratory - SOFTWARELAB（软件创新实验室（SOFTWARELAB））；Dell Digital Services（戴尔数字服务公司）；Dell EMC（戴尔EMC公司）
An Intelligent Social Learning-based Optimization Strategy for Black-box Robotic Control with Reinforcement Learning
School of Marine Science and Technology, Northwestern Polytechnical University（西北工业大学海洋科学与技术学院）；College of Electrical Engineering and Control Science, Nanjing Tech University（南京工业大学电气工程与控制科学学院）
Advancing LLM-Based Security Automation with Customized Group Relative Policy Optimization for Zero-Touch Networks
National Engineering Research Center for Mobile Network Technologies, Beijing University of Posts and Telecommunications（移动网络技术国家工程研究中心，北京邮电大学）；Beijing University of Posts and Telecommunications（北京邮电大学）；Singapore University of Technology and Design（新加坡科技设计大学）；Department of Electronic Engineering, Kyung Hee University（韩国庆熙大学电子工程系）
Connecting Large Language Models with Blockchain: Advancing the Evolution of Smart Contracts from Automation to Intelligence
Key Lab of Education Blockchain and Intelligent Technology, Ministry of Education, China（中国教育部教育区块链与智能技术重点实验室）；School of Computer Science and Engineering, Guangxi Normal University, China（中国广西师范大学计算机科学与工程学院）
