Advanced Control Techniques for Embodied Intelligent Robots Under Uncertain Working Conditions

Chair:
Shaoxin Sun Chongqing University, China

Key Words: Embodied Intelligent Robots, Uncertain Environment, Robust Control, Sim-to-Real Migration, Advanced Control, Multimodal Perception

Information: Diverse uncertain working conditions widely exist during the actual operation of embodied intelligent robots, which brings great difficulties to the stable operation of robot equipment. As robots are increasingly applied to diversified complex industrial and unmanned scenarios, dynamic interference, system switch and input saturation greatly restrict the operational reliability of robot systems. In recent years, adaptive Sim-to-Real based on neural networks and pre-training robust control have evolved into mainstream novel control technologies for robotic optimization. This invited session aims to gather relevant researchers and engineering practitioners to exchange frontier progress on theoretical modeling, algorithm development, hardware deployment and practical verification of robot control technologies, facilitate academic exchanges and advance the engineering transformation of advanced control theories for embodied intelligent robots across industrial automation and unmanned equipment fields.

Topics of interest include but are not limited to: 

• Latest Research Progress of Robot Control in Uncertain Scenarios
• Algorithm Mechanism Design of Neural Network Driven Sim-to-Real and Pre-trained Robust Control
• Engineering Realization and Experimental Verification of Advanced Robot Control Schemes
• Closed-Loop Control Construction Based on Multimodal Perception Fusion
• Key Bottlenecks of Zero-Shot Adaptation and Dynamic Path Planning for Robots
  

Submission Deadline: June 30, 2026 (the second round)