Recent advances in sensing, computational intelligence, and big data analytics have been rapidly transforming and revolutionizing the manufacturing industry towards robot-rich and digitally connected factories. However, effective, efficient and safe coordination between humans and robots on the factory floor has remained a significant challenge. To meet the need for safe and effective human-robot collaboration in manufacturing, the investigators will research an integrated set of algorithms and robotic testbeds to sense, understand, predict and control the interaction of human workers and robots in collaborative manufacturing cells. It is expected that these methods will significantly improve the safety and productivity of hybrid human-robot production systems, thereby promoting their deployment in future "smart factories".
The project will address fundamental challenges in human-robot collaboration in the manufacturing environment, such as the limitation of one-to-one sensing between humans and robots, the lack of adaptive and stochastic modeling methods for reliable recognition and prediction of human actions and motions in different manufacturing scenarios, and multi-scale human-robot coordination. To address these challenges, multi-disciplinary research involving sensing, machine learning, stochastic modeling, robot path planning, and advanced manufacturing will be performed. Specific tasks include algorithm development and deployment on lab-scale and real-world testbeds to: (1) sense and recognize where objects (e.g., robots, humans, parts or tools) are located and what each worker is doing; (2) predict what the next human action will be; and (3) plan and control safe and optimal robot trajectories for individualized on-the-job assistance for humans, proactively avoiding worker injury.
The project will be based in the Industry 4.0 lab at The University of Auckland (https://lisms.auckland.ac.nz/
), working with colleagues at the Industrial Artificial Intelligence Research Group (https://iai.auckland.ac.nz
The successful candidate will receive comprehensive research training including technical, personal and professional skills.
• Academic background in mechatronics, mechanical or control, and automation;
• Strong mathematical and programming skills;
• Excellent communication skills and ability to interact professionally and productively in a team environment. Can-do attitude.
HOW TO APPLY
To apply for this position, please:
1. Send your cover letter, CV, academic transcripts and publication list to Dr. Yuqian Lu ([email protected]
) to find out more about this project.
2. Apply online at https://www.auckland.ac.nz/en/study/applications-and-admissions/how-to-apply/postgraduate-admission/doctoral-applications.html
Duration of study: Full-Time – between three and three and a half years fixed term.