Human-AI Collaborative Design (HI-CoDe) Group
Assistant Professor Song Binyang
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Research Vision
The research group aims to harness generative AI to optimise robot design and improve human-robot collaboration
Core Research Areas
The research group aims to harness generative AI to optimise robot design and improve human-robot collaboration
Core Research Areas
- Data-driven robotic linkage design leveraging Generative AI
- Topology optimisation and Generative AI to advance robotic design
- AI-driven drone fleet design and operations
- Design of interactive and adaptable robots for enhanced human-robot collaboration such as adaptable robots and large language model-based system
- AI can increase efficiency of design of complex and optimised robotic linkage mechanisms
- Optimised topology enables robots to have lightweight structures, material efficiency, improved mechanical performance, customisation for specific applications, integration with additive manufacturing, enhanced motion and dynamics, cost reduction and more.
- Drones designed or integrated with AI can lower costs and improve efficiency in applications such as logistics
- Adaptable robots can be tailored for different users, enabling scalable customisation and personalisation