Open-sourced kinematic models of the da Vinci Surgical System have previously been developed using serial chains for forward and inverse kinematics. However, these models do not describe the motion of every link in the closed-loop mechanism of the da Vinci manipulators; knowing the kinematics of all components in motion is essential for the foundation of modeling the system dynamics and implementing representative simulations. This paper proposes a modeling method of the closed-loop kinematics, using the existing da Vinci kinematics and an optical motion capture link length calibration. Resulting link lengths and DH parameters are presented and used as the basis for ROS-based simulation models. The models were simulated in RViz visualization simulation and Gazebo dynamics simulation. Additionally, the closed-loop kinematic chain was verified by comparing the remote center of motion location of simulation with the hardware. Furthermore, the dynamic simulation resulted in satisfactory joint stability and performance. All models and simulations are provided as an open-source package.
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A sEMG Proportional Control for the Gripper of Patient Side Manipulator in da Vinci Surgical System
There is a large community of people with hand disabilities, and these disabilities can be a barrier to those looking to retain or pursue surgical careers. With the development of surgical robotics technologies, it may be possible to develop user interfaces to accommodate these individuals. This paper proposes a hand-free control method for the gripper of a patient side manipulator (PSM) in the da Vinci surgical system. Using electromyography (EMG) signals, a proportional control method was tested on its ability to grasp a pressure sensor. These preliminary results demonstrate that the user can reliably control the grasping motion of the da Vinci PSM using this system. There is a strong correlation between grasping force and normalized EMG signal (r= 0.874). Moreover, the gripper can generate a step grasping force output when feeding in a generated step signal. The results in this paper demonstrate the system integration of a research EMG system with the da Vinci surgical system and are a step towards developing accessible teleoperation systems for surgeons with disabilities. Hand-free control for remaining degrees of freedom in the PSM is under development using additional input from the motion capture system.
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- PAR ID:
- 10355675
- Date Published:
- Journal Name:
- 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society
- Page Range / eLocation ID:
- 4843 to 4848
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/EMBC48229.2022.9871664
