(Include but not limited to)
Track 1: Embodied Intelligence
Embodied Artificial Intelligence Architecture
Multimodal Perception
Human-Machine Interaction
Demonstration Learning
Cognitive Modeling
Adaptive Decision-Making
Knowledge Representation
Interpretable Artificial Intelligence
Social Perception-Based Artificial Intelligence
Emotion Recognition
Natural Language Understanding
Trust and Ethics of Embodied Artificial Intelligence
Lifelong Learning
Multisensory Fusion
Human-Centered Embodied Systems
Deep Reinforcement Learning for Embodied Intelligence
Curiosity-driven Autonomous Exploration
Imitation Learning and Behavior Cloning
Multi-task Learning and Lifelong Learning
Sample Efficiency and Generalization Ability of Robots
Causal Reasoning in Physical Systems
Track 2: Robot Perception
Visual-Linguistic-Action Large Models
Application of Multimodal Foundation Models in Robots
World Model and Environment Prediction
Decision-Making and Reasoning Driven by Foundation Models
Data and Simulation of Robot Basic Models
Efficient Adaptation of Large Models on Real Robots
Object Recognition, Visual Tracking
Posture and Gesture Recognition
Face and Expression Recognition
Image Segmentation and Classification
Optical and Photon Sensors
Lidar and Depth Perception
Tactile and Force Sensing Sensors
Sensor Fusion and Integration
Environment and Proximity Perception
Multimodal Perception System
3D Vision and Reconstruction
Real-Time Sensing and Image Analysis
Adaptive Perception Strategies
Track 3: Human-Machine Interaction
Human-Machine Collaboration
Human-Artificial Intelligence Collaboration
Multimodal Interaction
Emotional Interaction
Intelligent Human-Machine System
Reinforcement Learning in Closed-Loop Human-Machine Systems
Multimodal Intent Prediction
Guardian Agents
Digital Twin Humans
Action Recognition System
Brain-Computer Interface
Universal and Contextual Sensing Computing
Interpretable AI ......