The pose control for BMA-actuated soft EAR robot under external forces.

为了简化机器人的临床平移，本研究的目标是研究这种软机器人解决方案的新控制策略，以获得更大的转向能力、主动稳定和运动抑制，例如通过调节施加的接触力。为了实现这一目标，将研究新的基于视觉的反馈技术，以增强膜驱动软机器人的可控性。软体机器人的控制策略也将为此目标而发展。因此，新的控制方法，以确保机器人与周围环境的接触将被研究。由此产生的方法将被投入使用，例如调整系统的机械阻抗以实现成功的过程交付。博士议程主要分为三个部分。首先，机器人的姿态控制将使用用于描述机器人机械结构的传感变量（固有传感变量）来实现。由于基于内在感知的控制可能会产生错误的结果，因此机载摄像头将用于实现视觉与内在感知相结合的混合控制。在博士学位的最后阶段，除了前面提到的要点外，还将考虑患者和外科医生的动作，并对其进行反击，以实现现实的控制技术。

In order to simplify the robot's clinical translation, the goal of this research is to investigate new control strategies for this soft robotic solution to obtain greater steering capabilities, active stabilization, and motion suppression, for example by modulating the applied contact force. To achieve this, new vision-based feedback techniques will be investigated in order to enhance the controllability of membrane-actuated soft robots. Control strategies for the soft robot will also be developed for this aim. Therefore, new control methods for ensuring contact between the robot and its surroundings will be investigated. The resulting methods will then be put to use, such as adapting the mechanical impedance of the system to enable successful process delivery. The Ph.D. agenda is mainly divided into three sections.Firstly, the pose control of the robot will be implemented using sensing variables used to describe the mechanical configuration of the robot (intrinsic sensing variables). Since intrinsic sensing-based control could potentially give erroneous results, an onboard camera will be used to implement a hybrid control combining vision with intrinsic sensing. In the last stage of the Ph.D., in addition to the previously mentioned points, patient and surgeon movements will be taken into account and countered for achieving a realistic control technique.