Summary: Nature's creatures have inspired and helped develop many contemporary human technologies. The real advancement of the world is only possible with the inspiration gained through animal models. In recent years, intelligent bionic robots have made rapid progress. They are developed to play a more and more important role in hard-working environments, rescue missions, space exploration, and other fields. However, many problems still need to be solved for intelligent bionic robots. Especially in unknown environments, robots' sensing data is heavily affected by light, moving objects, and measurement uncertainties. Furthermore, multiple sensing data must be fused, and the complexity of many algorithms is prohibitively high for real-world applications. As a result, more approaches to simulation, control, and optimization need to be proposed and studied for intelligent bionic robots.
Sensing, Planning, and Control of Intelligent Bionic Robots
Large-Scale Robots Intelligence
2. Quality Engineering for Robotics/LLM
Summary: In recent years, the application of robots (especially in LLM) has become more and more common, not only in automotive welding, warehousing and logistics, indoor distribution, production line assembly and other fields, but also in surgery, urban emergency security, complex environment detection, etc. It is required that the robots are operated accurately, interact friendly, and with high performance, safety, and reliability in these application areas, which puts a serial of demands on the high quality of robots, thus the development and maintenance of robots is facing agreat challenges. Therefore, we set up the "Quality Engineering for Robotics/LLM" workshop to bring together researchers and industry practitioners in this field to discuss performance engineering, safety engineering, reliability engineering, user experience (UX) engineering for robotics & LLM. It also includes design, analysis and testing to improve the quality of this area.
Reliability or Resilience design of robots UX design of robots/LLM Performance testing of Robots/LLM Reliability or stability testing of robots/LLM Fault Injection Experiment or Chaos Engineering Real-time testing and analysis of robots (Network) Penetration testing of Robots/LLM Robot-oriented simulation testing Security risk assessment of robots/LLM Interactive UX evaluation of robots/LLM LLM measurement criteria and data sets Testing tools for robots/LLM
3. Intelligent Software Engineering
Summary: With the rapid development of artificial intelligence, artificial intelligence has been more and more widely used in the field of software engineering. The related research fields include: intelligent software IP, software artifact knowledge base, intelligent question and answering system, intelligent code generation and completion, intelligent document generation and completion, intelligent software system integration, intelligent malware detection, intelligent testing, and so on. The application of artificial intelligence in software engineering will reduce the costs of software development and maintenance, and improve the efficiency and quality of software development.
Design and implementation of intelligent software IP
Design and construction of Software artifact knowledge base Intelligent question and answering system related to software engineering Intelligent recommendation related to software engineering Intelligent code generation and completion Intelligent document generation and completion Intelligent software system integration Intelligent malware detection Intelligent software testing and defect prediction