Abstract
To reduce the risk of infection in medical personnel working in infectious-disease areas, we proposed a hyper-redundant mobile medical manipulator (HRMMM) to perform contact tasks in place of healthcare workers. A kinematics-based tracking algorithm was designed to obtain highly accurate pose tracking. A kinematic model of the HRMMM was established and its global Jacobian matrix was deduced. An expression of the tracking error based on the Rodrigues rotation formula was designed, and the relationship between tracking errors and gripper velocities was derived to ensure accurate object tracking. Considering the input constraints of the physical system, a joint-constraint model of the HRMMM was established, and the variable-substitution method was used to transform asymmetric constraints to symmetric constraints. All constraints were normalized by dividing by their maximum values. A hybrid controller based on pseudo-inverse (PI) and quadratic programming (QP) was designed to satisfy the real-time motion-control requirements in medical events. The PI method was used when there was no input saturation, and the QP method was used when saturation occurred. A quadratic performance index was designed to ensure smooth switching between PI and QP. The simulation results showed that the HRMMM could approach the target pose with a smooth motion trajectory, while meeting different types of input constraints.
摘要
为降低医务人员在传染病区域工作的感染风险, 提出了采用超冗余移动医疗机械臂(HRMMM)代替医务人员在医疗服务中执行接触性任务。设计了一种基于运动学的姿态跟踪算法, 以实现高精度的位姿跟踪。建立了HRMMM 的运动学模型, 推导了其整体雅可比矩阵。为了保证准确的目标跟踪, 设计了基于罗德里格斯旋转公式的跟踪误差, 并推导了跟踪误差与夹爪速度之间的关系。考虑到物理的输入约束, 建立了HRMMM 的关节约束模型, 采用变量替换法将非对称约束转换为对称约束, 所有约束都通过除以其最大值进行无量纲化。为了满足医疗事件中的实时运动控制要求, 设计了一种基于伪逆(PI)和二次规划(QP)的混合控制器, 无输入约束饱和时采用PI 方法, 出现约束饱和时采用QP 方法。设计二次性能指标保证PI 和QP 之间的平滑切换。仿真结果表明HRMMM 可以在满足在不同类型的输入约束情况下, 以平滑的运动轨迹接近目标姿态。
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Abbreviations
- D :
-
Normalized matrix
- e :
-
Pose error
- ê :
-
Joint position error
- f :
-
Coefficient vector
- H :
-
Coefficient matrix
- J :
-
Global Jacobian matrix
- J o :
-
Jacobian matrix of the lifting manipulator
- L P :
-
Pose-error interaction matrix
- L R :
-
Rotating interaction matrix
- p e :
-
Initial gripper pose
- p * e :
-
Target gripper pose
- (p x ,P y ,P z):
-
Gripper position
- q :
-
Joint position vector
- q 0 :
-
Joint position vector at the previous moment
- \(\dot{q}\) :
-
Joint velocity vector
- \(\overline{\dot{q}}\) :
-
Joint velocity vector with variable substitution
- R :
-
Rotation matrix
- t :
-
Position vector
- T :
-
Homogeneous transformation matrix
- U o :
-
Normalized double-ended constraint
- v :
-
Linear velocity
- V e :
-
Gripper velocity in the gripper coordinate system
- V g :
-
Gripper velocity in the world coordinate system
- α :
-
Heading angle
- ζ :
-
State of the mobile platform
- θ :
-
Joint angle
- θu :
-
Rotation vector
- ξ :
-
Double-ended constraint
- (ϕ x, ϕ y, ϕ z):
-
Gripper attitude
- ω :
-
Angular velocity
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Foundation item: the National Natural Science Foundation of China (No. 52175103)
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Zhang, K., Chen, L. & Dong, Q. Input-Constrained Hybrid Control of a Hyper-Redundant Mobile Medical Manipulator. J. Shanghai Jiaotong Univ. (Sci.) 28, 348–359 (2023). https://doi.org/10.1007/s12204-023-2580-4
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DOI: https://doi.org/10.1007/s12204-023-2580-4
Key words
- input-constrained hybrid control
- hyper-redundant mobile medical manipulator (HRMMM)
- pseudoinverse (PI)
- quadratic programming (QP)
- pose tracking