The CR Lab facilitates a number of robotics research projects. Our projects are diverse and span a range of applications and technologies. We are always looking for new opportunities to collaborate and expand our research network. If you are interested in partnering with us, please get in touch.

The Robots, Art, People and Performance Laboratory (RAPP Lab) is conceived as a living laboratory that functions as an experimental sandbox where roboticists and artists converge to explore the untapped possibilities of human-robot interaction through the lens of performance. Through structured workshops and public performances, RAPP Lab examines how robots can transition from mere technological tools to active participants in cultural expression.

Human beings possess a unique and highly evolved capacity to dynamically regulate their level of social presence in response to environmental cues, social norms, and contextual expectations—a capability that plays a crucial role in shaping Human-Robot Interaction (HRI). Yet, its modulation remains an underexplored area in embodied robotic systems. This research advances the field by systematically redefining social presence within HRI and developing a novel framework for its dynamic modulation.

This thesis investigates the cognitive potential of embodied robotics, offering a novel perspective by interpreting robotic behaviour through the lens of human-like cognition. It addresses a key gap in current methodologies, which often assess isolated cognitive abilities without accounting for the inherently interconnected nature of cognition in intelligent systems.

In Australia, an alarming 75.8 million tonnes of waste is generated annually, with organic waste contributing approximately 14.4 million tonnes. Food waste, a major component of organic waste, accounts for 32.6% and is predominantly disposed of in landfills, where it generates methane, a greenhouse gas with a global warming potential at least 28 times higher than carbon dioxide.

The Multiple Sensors Multi-instance (MSMI) Dataset represents a comprehensive collection of multi-sensor data designed to support research in robotics and machine learning applications. This dataset addresses the growing need for diverse, multi-modal data sources in the development of robust robotic systems.

Concurrent developments in robotic design and natural language processing (NLP) have enabled the production of humanoid chatbots that can operate in commercial and community settings. Though still novel, the presence of physically embodied social robots is growing and will soon be commonplace. Our study is set at this point of emergence, investigating people’s first impressions of a humanoid chatbot in a public venue.

The aged care industry is under pressure from stressors including increasing resident numbers and difficulty meeting staffing requirements. Robots may be able to support the industry by filling many vital roles, however it is currently unclear how successful implementation of robots in aged care can occur, and detailed in situ assessment and mapping of robotic deployment in these settings is lacking. The current case study examines early-stage implementation of robots at an aged care home in Australia, assessing logistical, technical and person factors.

This study explores the impact of appearance and speech on human perceptions of faces in human-robot interactions. Three videos were generated depicting the real face of an artist and two virtual versions of the same artist, with increasing resolution and fidelity. Each video was presented with and without speech, with matching levels of fidelity to the faces.

This project focuses on the development of the Synthetic Operating Room Table (SORT) Dataset, designed to support research in medical robotics and surgical automation. The dataset provides synthetic data for training and evaluating robotic systems in operating room environments.