Assistive robotic systems endeavour to support those with movement
disabilities, enabling them to move again and regain functionality. Main issue
with these systems is the complexity of their low-level control, and how to
translate this to simpler, higher level commands that are easy and intuitive
for a human user to interact with. We have created a multi-modal system,
consisting of different sensing, decision making and actuating modalities,
leading to intuitive, human-in-the-loop assistive robotics. The system takes
its cue from the user's gaze, to decode their intentions and implement
low-level motion actions to achieve high-level tasks. This results in the user
simply having to look at the objects of interest, for the robotic system to
assist them in reaching for those objects, grasping them, and using them to
interact with other objects. We present our method for 3D gaze estimation, and
grammars-based implementation of sequences of action with the robotic system.
The 3D gaze estimation is evaluated with 8 subjects, showing an overall
accuracy of $4.68\pm0.14cm$. The full system is tested with 5 subjects, showing
successful implementation of $100\%$ of reach to gaze point actions and full
implementation of pick and place tasks in 96\%, and pick and pour tasks in
$76\%$ of cases. Finally we present a discussion on our results and what future
work is needed to improve the system.