Vision-based Control of a Soft Robot for Maskless Head and Neck Cancer Radiotherapy

TL;DR

This paper presents a vision-based control system for a soft robot to accurately position patients' heads during maskless radiotherapy for head and neck cancer, using sensor fusion and LQG control.

Contribution

It introduces a novel control approach combining RGB-D sensor fusion, system identification, and LQG control for soft robot-based patient positioning.

Findings

Successful head pitch control demonstrated in experiments

Effective sensor fusion improves head position estimation

Linear quadratic Gaussian control achieves precise manipulation

Abstract

This work presents an on-going investigation of the control of a pneumatic soft-robot actuator addressing accurate patient positioning systems in maskless head and neck cancer radiotherapy. We employ two RGB-D sensors in a sensor fusion scheme to better estimate a patient's head pitch motion. A system identification prediction error model is used to obtain a linear time invariant state space model. We then use the model to design a linear quadratic Gaussian feedback controller to manipulate the patient head position based on sensed head pitch motion. Experiments demonstrate the success of our approach.