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Intelligence & Robotics (IR)

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Publisher:
OAE Publishing
Publisher Account:
ISSN:
2770-3541
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Call For Papers

Intelligence & Robotics (IR) is an academic journal published by OAE Publishing. (ISSN 2770-3541).

Intelligence & Robotics publishes top-quality unpublished original technical and non-technical application-focused articles on intelligence and robotics, particularly on the interdisciplinary areas of intelligence and robotics. The Journal seeks to publish articles that deal with the theory, design, and applications of intelligence and robotics, ranging from software to hardware. The Journal would be interested in the distributed development and maintenance of real-world intelligent and robotic systems by multidisciplinary teams of scientists and engineers. ◆Homepage: https://www.oaepublish.com/ir ◆Editor-in-Chief: Prof. Simon X. Yang, University of Guelph, Fellow of the Canadian Academy of Engineering ◆IF: 3.9 | CiteScore: 5.8 The scope includes, but is not limited to: 1. Artificial Intelligence Foundations & Methods ●Machine learning and deep learning ●Generative AI and foundation models (e.g., large language models, vision-language models) ●Reinforcement learning and imitation learning ●Self-supervised, unsupervised, and continual/lifelong learning ●Causal inference and explainable AI (XAI) ●Trustworthy, robust, and secure AI (adversarial learning, OOD generalization) ●Neuro-symbolic AI and hybrid intelligence ●Swarm intelligence and distributed intelligence 2. Embodied Intelligence & Physical AI ●Embodied AI and embodied cognition ●Foundation models for robotics (robot foundation models, VLA models) ●Perception–action loop and sensorimotor learning ●Sim-to-real transfer and domain adaptation ●Interactive learning in physical environments ●World models and predictive representations for agents 3. Robotics: Modeling, Planning, and Control ●Motion planning and trajectory optimization ●Autonomous navigation and SLAM ●Multi-agent systems and cooperative control ●Distributed coordination and consensus control ●Fault diagnosis, fault-tolerant control, and resilient robotics ●Human-in-the-loop control and shared autonomy ●Learning-based control and adaptive control systems 4. Robot Perception & Multimodal Intelligence ●Computer vision for robotics (3D vision, scene understanding) ●Multimodal perception and sensor fusion (vision, language, tactile, audio) ●Semantic mapping and spatial intelligence ●Active perception and attention mechanisms ●Event-based perception and neuromorphic sensing 5. Human–Robot Interaction & Collaboration ●Human–robot collaboration (HRC) ●Teleoperation and telepresence systems ●Intention recognition and behavior prediction ●Natural language interaction and dialogue systems for robots ●Social robotics and affective computing ●Brain–computer interfaces (BCI) for robotic control 6. Advanced Robotic Systems & Platforms ●Humanoid robots and legged robots ●Aerial, ground, marine, and space robots ●Swarm robotics and multi-robot systems ●Soft robotics and bio-inspired robotic systems ●Surgical robotics and medical robotic systems ●Industrial and service robotics 7. Digital, Virtual, and Simulation Technologies ●Digital twins for robotics and intelligent systems ●Simulation platforms and virtual testing environments ●Virtual reality (VR), augmented reality (AR), and mixed reality (MR) ●Data-driven simulation and synthetic data generation 8. AI for Cyber-Physical and Intelligent Systems ●Autonomous driving and intelligent transportation systems ●Smart manufacturing and Industry 4.0 ●Intelligent infrastructure and smart cities ●Marine and aerospace autonomous systems ●Edge AI and embedded intelligence 9. Reliability, Prognostics, and Health Management for Robotic Systems ●Fault diagnosis and fault-tolerant systems ●Remaining useful life (RUL) prediction ●AI-based battery health estimation (SOH, SOC) ●Predictive maintenance for robotic and autonomous systems ●Digital twin-driven health monitoring 10. The journal encourages interdisciplinary research on artificial intelligence and/or robotics ●Energy systems ●Healthcare ●Transportation ●Manufacturing ●Other emerging domains
Last updated by Intelligence & Robotics on

Special Issues

Special Issue on Intelligent Locomotion and Robot–Terrain Interaction: Embodied and Physical Intelligence for Mobile Robots Submission Date: 2027-08-31 Special Topic Homepage: https://www.oaepublish.com/specials/ir.10594 ◆Special Topic Introduction Intelligent locomotion and robot–terrain interaction are fundamental to enabling mobile robots to operate safely, efficiently, and autonomously in complex, unstructured, and extreme environments. Unlike robots operating in well-structured settings, legged and wheeled robots in natural environments must continuously perceive terrain conditions, understand the physical interactions between the robot and its surroundings, and adapt their motion according to changing environmental constraints. Integrating perception, interaction, learning, and control is therefore essential for developing embodied and physical intelligence that can support robust mobility in the real world. This Special Topic aims to bring together recent advances in intelligent locomotion, robot–terrain interaction, embodied intelligence, and physical intelligence for legged and wheeled robots. Topics of interest include terrain and environmental perception, terramechanics, multimodal sensing, robot learning, adaptive locomotion, motion planning, autonomous navigation, and physical interaction with complex terrains. Contributions addressing field robotics, planetary exploration, and other challenging environments are particularly encouraged, with an emphasis on methods that enable robots to learn from physical interactions and achieve robust, adaptive, and intelligent locomotion. Topics include, but are not limited to: ● Intelligent Locomotion and Motion Control; ● Robot–Terrain Interaction and Terramechanics; ● Embodied and Physical Intelligence for Mobile Robots; ● Terrain and Environmental Perception; ● Multimodal Sensing and Physical Interaction; ● Robot Learning and Adaptive Locomotion; ● Learning-Based Motion Planning and Control; ● Autonomous Navigation in Complex Environments; ● Legged and Wheeled Mobile Robots; ● Field and Planetary Exploration Robotics; ● Adaptive and Robust Locomotion; ● Human–Robot Interaction and Teleoperation. Keywords Intelligent locomotion, robot–terrain interaction, embodied intelligence;, physical AI, legged and wheeled robots, mobile robotics, terramechanics, physical property characterization, terrain perception, robot learning, adaptive locomotion, autonomous navigation, planetary exploration Guest Editors ●Prof. Liang Ding State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin, Heilongjiang, China. ●Prof. Hesheng Wang School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai, China. ●Assoc. Prof. Ruyi Zhou State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin, Heilongjiang, China. ●Prof. Tao Zhang School of Mechanical Engineering and Automation, Beihang University, Beijing, China. ●Dr. Lutz Richter SoftServe, Munich, Germany. Submission Information ●For Author Instructions, please refer to https://www.oaepublish.com/ir/author_instructions ●For Online Submission, please login at https://www.oaecenter.com/login?JournalId=ir&IssueId=ir26082810594 ●Submission Deadline: 31 Aug 2027 ●Contacts: Julia Wei, Science Editor, [email protected]
Last updated by Intelligence & Robotics on
Special Issue on Learning and Collective Intelligence for Multi-Robot Systems Submission Date: 2027-09-15 Special Topic Homepage: https://www.oaepublish.com/specials/ir.10598 ◆Special Topic Introduction Multi-robot systems are emerging as an important paradigm for enabling scalable, flexible, and intelligent autonomy in complex and dynamic environments. By allowing multiple robots to perceive, communicate, learn, and make decisions collectively, multi-robot systems can accomplish complex tasks more efficiently and robustly than individual robots. Recent advances in robot learning, multi-agent learning, reinforcement learning, distributed intelligence, and swarm intelligence have created new opportunities for developing autonomous robotic systems capable of adaptive coordination, collaborative decision-making, and collective behaviors. This Special Topic focuses on Learning and Collective Intelligence for Multi-Robot Systems, with the aim of bringing together the latest advances in robot learning, multi-agent learning, coordination, communication, decision-making, and distributed intelligence for collaborative robotic systems. Particular attention is given to how multiple robots can learn and acquire cooperative behaviors through interaction, share information efficiently, adapt to dynamic environments, and achieve collective capabilities beyond those of individual robots. Both multi-agent learning approaches and other learning-based methodologies for multi-robot systems are welcome. The Special Topic welcomes original research and review articles covering both fundamental methodologies and real-world applications. Topics of interest include multi-robot learning, multi-agent reinforcement learning, multi-robot coordination, collective and swarm intelligence, distributed decision-making, robot communication, heterogeneous multi-robot collaboration, cooperative perception and navigation, multi-robot planning and control, adaptive and continual learning, human–robot collaboration, and edge-enabled distributed intelligence for autonomous robotic systems. By bridging learning, collective intelligence, and robotics, this Special Topic aims to advance the development of scalable, robust, adaptive, and generalizable multi-robot systems for complex real-world environments. Topics include, but are not limited to: ● Multi-Robot Learning & Multi-Agent Learning; ● Reinforcement Learning for Multi-Robot Systems; ● Collective & Swarm Intelligence; ● Multi-Robot Coordination & Collaboration; ● Robot Communication & Distributed Decision-Making; ● Heterogeneous & Adaptive Multi-Robot Systems; ● Cooperative Perception & Distributed Sensing; ● Human–Robot Collaboration; ● Distributed & Edge Intelligence for Multi-Robot Systems; ● Learning-Based Applications in Multi-Robot Systems. Keywords Multi-robot learning, multi-agent learning, collective intelligence, multi-robot systems, multi-agent reinforcement learning, multi-robot coordination, distributed intelligence, swarm intelligence, heterogeneous multi-robot systems, cooperative perception, robot communication, autonomous robotics Guest Editors ●Prof. Bin Guo School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, China. ●Prof. Xuyang Chen School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, China. ●Prof. Qingkai Meng College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China. Submission Information ●For Author Instructions, please refer to https://www.oaepublish.com/ir/author_instructions ●For Online Submission, please login at https://www.oaecenter.com/login?JournalId=ir&IssueId=ir26090110598 ●Submission Deadline: 15 Sep 2027 ●Contacts: Julia Wei, Science Editor, [email protected]
Last updated by Intelligence & Robotics on

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