Adaptive assistive robotics: a framework for triadic collaboration between humans and robots
Daniel Gordon, Andreas Christou, Theodoros Stouraitis, Michael Gienger, Sethu Vijayakumar
Abstract
Robots and other assistive technologies have a huge potential to help society in domains ranging from factory work to healthcare. However, safe and effective control of robotic agents in these environments is complex, especially when it involves close interactions and multiple actors. We propose an effective framework for optimizing the behaviour of robots and complementary assistive technologies in systems comprising a mix of human and technological agents with numerous high-level goals. The framework uses a combination of detailed biomechanical modelling and weighted multi-objective optimization to allow for the fine tuning of robot behaviours depending on the specification of the task at hand. We illustrate our framework via two case studies across assisted living and rehabilitation scenarios, and conduct simulations and experiments of triadic collaboration in practice. Our results indicate a marked benefit to the triadic approach, showing the potential to improve outcome measures for human agents in robot-assisted tasks.