Topic: AI-Driven Intelligent Robotics and Autonomous Manufacturing Systems: Perception, Decision-Making, and Real-World Applications -from AIIM 2026 expanded submissions

Artificial intelligence is fundamentally reshaping the future of intelligent robotics and advanced manufacturing. Recent breakthroughs in foundation models, multimodal perception, embodied intelligence, machine learning, digital twins, and autonomous decision-making are enabling robotic systems to move beyond predefined automation toward adaptive, collaborative, and intelligent operation in complex real-world environments. Meanwhile, next-generation manufacturing systems increasingly rely on AI-powered robots capable of perception, planning, reasoning, learning, and human collaboration to achieve higher productivity, flexibility, and resilience.

The 6th International Symposium on Artificial Intelligence and Intelligent Manufacturing (AIIM 2026) brings together researchers from artificial intelligence, robotics, intelligent manufacturing, computer vision, industrial automation, intelligent control, and machine learning. The conference highlights emerging advances including intelligent sensing, autonomous robots, predictive maintenance, digital twins, industrial Internet of Things (IIoT), AI-driven quality inspection, human-robot collaboration, and intelligent decision-making.

This Special Issue aims to collect session keynote lecture abstracts, invited speech abstracts, all accepted oral and poster presentation abstracts, as well as high-quality extended versions of selected contributions presented at AIIM 2026, along with related submissions that reflect the latest progress in this rapidly evolving field.

Topics include, but are not limited to:

Embodied AI and intelligent robotic systems

● Foundation models and multimodal AI for robotics;

● Robot perception, scene understanding, and 3D vision;

● AI-enabled robot planning, reasoning, and decision-making;

● Autonomous manipulation and intelligent grasping;

● Industrial robotics and smart manufacturing;

● Human–robot collaboration and shared autonomy;

● Multi-robot systems and swarm intelligence;

● Robot learning, reinforcement learning, and imitation learning;

● Digital twins for robotic systems;

● Intelligent sensing and sensor fusion;

● Edge AI and real-time robotic intelligence;

● Predictive maintenance using AI;

● Industrial Internet of Things (IIoT) for robotic systems;

● Autonomous inspection and quality control;

● AI-powered robotic logistics and warehouse automation;

● Explainable, trustworthy, and safe AI for robotics;

● Robot simulation and sim-to-real transfer;

● Large vision-language-action models for robotics;

● Real-world deployment and industrial case studies of intelligent robotic systems.