The design of autonomous agents which can complete tasks in complex dynamic environments is a core area of research of modern artificial intelligence. A crucial requirement in such agents is the ability to interact competently with other agents (including humans) whose behaviours, beliefs, plans, and goals may be unknown. To interact with such agents requires the ability to reason about their unknown behaviours based on their observed actions, the context in which these actions took place, and other available information.
University of Edinburgh
Referential communication refers to how an agent communicates their intended meaning to another agent about a referent, or object. This is a crucial aspect of human-robot interaction, especially when the robot must collaborate with human users in order to help them perform a shared task.
The aim of the ‘MiniMat’ project is to develop a minimal animal-like soft robot and test its impact on vulnerable children in cruelty prevention and animal-assisted interventions (AAI). Intentional animal cruelty begins as young as 4 years of age, often by highly vulnerable children. MiniMat is required because of the ethical issues of using live animals in interventions with children who have harmed animals. Similarly, animal-assisted interventions can benefit vulnerable children’s mental health.
In real world applications, a large variety of jobs involve handling various objects as the core process. However, most of these jobs nowadays are still performed by people. One obvious fact of human manipulation is the use of two hands that cooperate to achieve some task. But not too much research has been done involving coordination and optimal use of two hands. At the system level, having two hands naturally introduces physical redundancy that provides extra layer of safety and reliability against malfunctions such as object slippage.
Research Background of the Project: Soft manipulators have recently gained significant recognition for their versatility and advantages over rigid-link systems. Their multi-DOF bending capabilities and their intrinsic compliance make them a viable technology for complex tasks where an enhanced degree of flexibility is required as well as locomotion tools for bioinspired robots. However, the complexity of these continuum actuators makes them hard to control and, consequently, less suited for everyday use in industrial, medical or other robotics applications.
A large variety of industrial applications strongly involve handling various objects as the core process for task completion. To date, most of these jobs are still performed by people. Although some are automated by robots, those solutions primarily reply on pre-designed rules or tele-operation (limited operational time due to cognitive overload), which unavoidably limits the performance in changing environments.
There is significant interest in characterising surgical skills in the form of detailed models that correlate hand movements, applied forces and the context of the shape and texture of tissues that are actually being manipulated.
Neuromuscular deficiencies often diminish gait coordination and in turn lead to a higher risk of fall. The patient’s interaction with the environment becomes unstable and unsafe and this has an effect on their confidence, overall health and quality of life. To minimise the adverse effects associated with gait impairments, apart from conventional therapy, robot-assisted physical therapy has gained attention where the safe human-robot interaction is essential.