TY - JOUR
T1 - Demonstration-Guided Pose Planning and Tracking for Multi-Section Continuum Robots Considering Robot Dynamics
AU - Seleem, Ibrahim A.
AU - Assal, Samy F.M.
AU - Ishii, Hiroyuki
AU - El-Hussieny, Haitham
N1 - Funding Information:
This work was supported by the Mission Department of the Ministry of Higher Education (MOHE) of Egypt for granting him scholarship to carry out his graduate studies with the Egypt-Japan University of Science and Technology.
Publisher Copyright:
© 2013 IEEE.
PY - 2019
Y1 - 2019
N2 - Recently, there has been an increased interest in the deployment of continuum robots in unstructured and challenging environments. However, the application of the state-of-the-art motion planning strategies, that have been developed for rigid robots, could be challenging in continuum robots. This, in fact, is due to the compliance that continuum robots possess besides their increased number of degrees of freedom. In this paper, a Demonstration Guided Pose Planning (DGPP) technique is proposed to learn and subsequently plan for spatial point-to-point motions for multi-section continuum robots. Motion demonstrations, including position and orientation, are collected from a human via a flexible input interface that is developed to command the continuum robot intuitively via teleoperation. A dynamic model based on Euler-Lagrange formalism is derived for a two-section continuum robot to be considered while planning for the robot motions. Meanwhile, a Proportional-Derivative (PD) computed torque controller with a Model Reference Adaptive Kinematic Control (MRAKC) scheme are developed to ensure the tracking performance against system uncertainties and disturbances. Also, the system stability analysis based on Lyapunov quadratic equation is proven. Simulation results prove that the proposed DGPP approach, along with the developed control scheme, have the ability to learn, generalize and reproduce spatial motions for a two-section continuum robot while avoiding both static and dynamic obstacles that could exist in the environments.
AB - Recently, there has been an increased interest in the deployment of continuum robots in unstructured and challenging environments. However, the application of the state-of-the-art motion planning strategies, that have been developed for rigid robots, could be challenging in continuum robots. This, in fact, is due to the compliance that continuum robots possess besides their increased number of degrees of freedom. In this paper, a Demonstration Guided Pose Planning (DGPP) technique is proposed to learn and subsequently plan for spatial point-to-point motions for multi-section continuum robots. Motion demonstrations, including position and orientation, are collected from a human via a flexible input interface that is developed to command the continuum robot intuitively via teleoperation. A dynamic model based on Euler-Lagrange formalism is derived for a two-section continuum robot to be considered while planning for the robot motions. Meanwhile, a Proportional-Derivative (PD) computed torque controller with a Model Reference Adaptive Kinematic Control (MRAKC) scheme are developed to ensure the tracking performance against system uncertainties and disturbances. Also, the system stability analysis based on Lyapunov quadratic equation is proven. Simulation results prove that the proposed DGPP approach, along with the developed control scheme, have the ability to learn, generalize and reproduce spatial motions for a two-section continuum robot while avoiding both static and dynamic obstacles that could exist in the environments.
KW - Continuum robots
KW - dynamic modeling
KW - dynamic movement primitives
KW - kinematic control
KW - motion planning
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U2 - 10.1109/ACCESS.2019.2953122
DO - 10.1109/ACCESS.2019.2953122
M3 - Article
AN - SCOPUS:85077572138
SN - 2169-3536
VL - 7
SP - 166690
EP - 166703
JO - IEEE Access
JF - IEEE Access
M1 - 8896877
ER -