Special Session 1: Advancements in Smart Robot applications for novel green environment
Chair: Wael A. Altabey, Alexandria University, Egypt |
Vice Chair: Mohamed A. Al-Moghazy, Alexandria University, Egypt |
| Smart robots are increasingly being utilized to create and maintain novel green environments, with advancements in AI and robotics enabling more efficient and sustainable practices. These applications span various sectors, including agriculture, waste management, and environmental monitoring, contributing to a more eco-friendly future.These advancements demonstrate the potential of smart robots to play a vital role in creating a more sustainable and environmentally friendly future. | 1. Smart Agriculture 1.1 Eco-Phenotyping: 1.2 Precision Agriculture: 1.3 Weed Control: 1.4 Greenhouse Automation: 2. Waste Management: 2.1 Smart Waste Sorting: 2.2 Automated Waste Collection: 2.3 Waste Reduction: 3. Environmental Monitoring: 3.1 Biodiversity Monitoring: 3.2 Environmental Data Collection: 3.3 Climate Change Research: 4. Other Green Applications: 4.1 Water Purification: 4.2 Soil Treatment: 4.3 Forestry and Conservation: 5. Key Advancements Driving these Applications: 5.1 Artificial Intelligence (AI) and Machine Learning: 5.2 Computer Vision: 5.3 Sensor Technology: |
Special Session 2: Recent Advancements in Emerging Embodied Perception Technologies of Robotics
Chair: Prof. Lei Yang, Zhengzhou University, China |
Vice Chair: Assoc. Prof. Yunkai Li, Zhengzhou University, China |
| Embodied perception, where intelligent agents understand the world through continuous interaction between their physical bodies, actions, and environments, is emerging as a pivotal paradigm for advancing robots from passive observers to active, context-aware participants. Recent breakthroughs in novel sensors, multimodal fusion algorithms, and embodied artificial intelligence have enabled robotic systems to achieve unprecedented levels of perceptual adaptability and situational understanding in dynamic, open-ended, and uncertain real-world settings. This session aims to bring together researchers and practitioners to showcase cutting-edge developments in embodied perception technologies that empower robots to operate effectively in complex, dynamic, and unstructured real-world environments. | 1 Multimodal Sensing and Fusion 1.1 Vision-Touch Integration 1.2 Audio-Visual Perception 1.3 Proprioceptive-Exteroceptive Fusion 2 Active and Interactive Perception 2.1 Perception through Interaction 2.2 Attention Mechanisms in Robotic Systems 2.3 Task-Oriented Sensing Strategies 3 Learning-Based Embodied Perception 3.1 Self-Supervised and Embodied Learning 3.2 Sim-to-Real Transfer for Perception 3.3 World Models and Predictive Coding 4 Applications and Platforms 4.1 Autonomous Navigation in Unstructured Environments 4.2 Human-Robot Interaction 4.3 Assistive and Service Robots with Adaptive Sensing |
Special Session 3: Intelligent Unmanned Systems: Perception, Control, and VLA Large Models
Chair: Heng Shi, Tsinghua University, China |
Vice Chair: Shuai Song, Henan University of Science and Technology, China |
| This workshop explores the transformative impact of Very Large-scale AI (VLA) models on intelligent unmanned systems across various domains. It focuses on the integration of cutting-edge perception, control, and VLA models to achieve advanced autonomy and performance in unmanned vehicles and robotic systems. The workshop will cover the latest advancements in VLA-driven perception, enabling unmanned systems to understand and interpret complex environments with unprecedented accuracy and robustness. This includes topics such as object detection, scene understanding, semantic segmentation, and multimodal sensor fusion, all enhanced by the power of large-scale pre-trained models. Furthermore, the workshop will delve into the application of VLA models for intelligent control of unmanned systems. This encompasses areas such as reinforcement learning, imitation learning, and model-based control, where VLA models are leveraged to learn optimal control policies and adapt to dynamic environments. We will also explore the use of VLA models for task planning, decision-making, and human-robot interaction, empowering unmanned systems to perform complex tasks autonomously and safely. The workshop aims to bring together researchers and practitioners from academia and industry to discuss the challenges and opportunities of applying VLA models to intelligent unmanned systems. It will feature presentations on the latest research findings, innovative applications, and future directions in this rapidly evolving field. Keynote speakers will share their insights on the potential of VLA models to revolutionize the field of unmanned systems, enabling a new generation of intelligent and autonomous machines. This workshop will foster collaboration and knowledge exchange, accelerating the development and deployment of intelligent unmanned systems powered by VLA models. | 1 Unmanned Systems 2 Autonomous Systems 3 Intelligent Systems 4 VLA Large Models 5 Artificial Intelligence 6 Perception 7 Control 8 Reinforcement Learning 9 Planning 10 Robotics 11 Sensor Fusion |