Biologically Inspired Robotics: Intelligent Systems for Trustworthy Human-Robot Co-learning and Adaptation

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Human-robot interactions are increasingly important in applications where intelligent systems provide assistance to or work alongside people. The ultimate goal of this research program is to develop novel biologically-inspired mechanisms for intelligent system design, enabling intelligent, autonomous robots to engage with people in joint-tasks facilitating co-learning and co-adaptation. Specific objectives over the next 5 years of this program are a) the development of appropriate co-learning computational mechanisms for trustworthy robots that learn and adapt in real-time, b) the study of the impact of robot embodiment, errors, and other factors relevant in establishing, maintaining and repairing human-robot trust, and integrating those factors into computational architectures that can sustain long-term human-robot interaction, c) design of computational mechanisms for robots that can assess and convey (e.g. visualise) their level of competence and confidence in their own learning and decision making, in order to improve human-robot trust, and d) to develop computational, behavioural models for creating trustworthy robot behaviour in terms of the robot's use of social cues and interaction modalities. Experimental evaluation of the architectures and algorithms will involve technical evaluation as well as validation in user studies. Outcomes of this work are expected to change the way social and intelligent autonomous robots interact with people. Methodologically, my work is using diverse methods from Artificial Intelligence, Human-Computer and Human-Robot Interaction. A novelty of this research program is to take inspiration from human/animal behaviour and then design computational models for social and intelligent robots. Biological models of communication and interaction are more universally and readily understood, which can yield more robust and efficient means of communication, and to generalize better across different robot embodiments, compared to the common focus on humanoid/ android robots that evoke high expectations in people in terms of the system's capabilities, but often lead to disappointment when expectations are not met. Outcomes of this program will significantly advance computer science and engineering towards creating robotic systems that people can "naturally" and efficiently interact with, and that they will trust. The project will train HQP in developing fundamental solutions to the development of trustworthy, social and intelligent robots. It will significantly advance the students' interdisciplinary knowledge and skills needed for a future career in academia or industry, where project results can potentially transform the use of such systems in real-world application areas, e.g. the care or service sectors in Canada.