Demonstration-Guided Pose Planning and Tracking for Multi-Section Continuum Robots Considering Robot Dynamics

Abstract

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. INDEX TERMS Continuum robots, motion planning, dynamic movement primitives, kinematic control, dynamic modeling.

Imitation-Based Motion Planning and Control of a Multi-Section Continuum Robot Interacting With the Environment

“…..T . Then, the phase variable s is computed by integrating the differential (13), then the target forces can be computed easily from ( 4) and ( 10) respectively. The problem is now addressed as a local weighted regression problem that could be solved based on linear least squares to get the weights W i and μ i .…”

“…In addition, in many medical applications, having a direct contact with the robot through kinesthetic teaching could be challenging. In our previous work [13], [14], a Demonstration Guided Pose Planning (DGPP) approach and control of a two-section continuum robot were proposed. The human demonstrations were recorded using a low accuracy Inertial Measurement Unit (IMU).…”

“…The human demonstrations were recorded using a low accuracy Inertial Measurement Unit (IMU). In [13], a rotation matrix representing orientation suffered from singularity at specific configurations. In addition, the computed torque with adaptive kinematic control was applied to track the robots' tip position, which was not efficient while interacting with the environment.…”

Plant-Inspired Soft Growing Robots: A Control Approach Using Nonlinear Model Predictive Techniques

“…Consequently, there is a critical need for innovative materials and locomotion systems in robotics to navigate these challenging environments effectively. Drawing inspiration from biological systems like elephant trunks, octopus tentacles, and snakes, the development of soft continuum robots featuring continuous bending backbones has facilitated non-destructive navigation in congested spaces [3][4][5]. However, the limited lengths of traditional continuum robots restrict their capacity to explore more distant spaces [6].…”

Development and Stability Analysis of an Imitation Learning-Based Pose Planning Approach for Multi-Section Continuum Robot

“…Based on the authors' previous work [25]- [27], a Demonstration-Guided Pose Planning (DGPP) approach was established to control the pose of the robot's end-effector considering the two-section robot dynamics. To control this pose, the developed controller was applied separately on the position and orientation of the robot end-effector which is considered a time consuming and not applicable in critical applications.…”