Motion Planning and Control of Artificial Muscle Actuated Underwater Vehicle Using Nonlinear Neural Oscillator

2007 ◽  
Author(s):  
Joon Soo Lee ◽  
Woosoon Yim ◽  
Kwang J. Kim
Keyword(s):  
Motion Planning ◽  
Controller Design ◽  
Artificial Muscle ◽  
Underwater Vehicle ◽  
Open Loop ◽  
Neural Oscillator ◽  
Aquatic Environments ◽  
Metal Composite ◽  
Planning And Control ◽  
And Control

In this paper, we introduce the motion planning and control strategy for the underwater vehicle actuated by a soft artificial muscle actuator. The artificial muscle used for this underwater application is an Ionic Polymer Metal Composite (IPMC) which can generate bending motion in aquatic environments. In this research, the double ring structured nonlinear neural oscillator is proposed for the undulatory motion in the actuator. The overall dynamic model of the flexible IPMC actuator including its fluid interaction terms is used for the motion planning and open-loop controller design. The IPMC used in this study is a patterned or segmented type where the electrode surface of the actuator is encoded such that each segment can be controlled independently for effectively generating an undulatory motion in the water. Computer simulations show that the proposed neural oscillator based controller can be effectively used for the underwater locomotion applications, and can be extended to the closed-loop controller where the precise maneuver is needed in the unstructured aquatic environments.

Path Planning and Control for Underwater Vehicle Driven by an Ionic Polymer Metal Composite (IPMC) Actuator

2010 ◽  
Author(s):  
Shivakanth Gutta ◽  
Woosoon Yim ◽  
Mohamed B. Trabia
Keyword(s):  
Path Planning ◽  
Objective Function ◽  
Underwater Vehicle ◽  
Trajectory Control ◽  
Planning Problem ◽  
Metal Composite ◽  
Penalty Term ◽  
Planning And Control ◽  
Polymer Metal ◽  
And Control

This paper presents an approach for trajectory planning and control of an underwater vehicle within obstacles. The vehicle is driven by a single IPMC actuator that goes through oscillatory locomotion. The presented work is divided into kinematic path planning and trajectory control sections. In the kinematic path planning phase, the vehicle is approximated by a rectangle that encloses the largest deformation of the oscillating IPMC actuator. Obstacles are approximated by polygonal shapes that approximate their actual dimensions. To simplify the problem of collision detection, vehicle is shrunk to a line while obstacles are expanded by a half width of the rectangle representing the vehicle. Path planning problem is formulated as a nonlinear programming problem that minimizes the error between current and goal configurations of the vehicle. The objective function combines the distance to target and the orientation of the vehicle. A penalty term is added to the objective function to ensure that the vehicle is not colliding with obstacles. The obtained path is discretized with respect to time, and controlled simultaneously for the yaw angle and speed of the vehicle. These two controllers are designed based on the simulation data from the dynamic model of the IPMC propelled vehicle. This proposed approach can be used in real time implementation of vehicle trajectory control in the presence of obstacles.

scholarly journals Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction

2021 ◽  
Author(s):  
Fahad Iqbal Khawaja ◽  
Akira Kanazawa ◽  
Jun Kinugawa ◽  
Kazuhiro Kosuge
Keyword(s):  
Motion Planning ◽  
Human Motion ◽  
Human Robot Interaction ◽  
Collaborative Robots ◽  
Sensing System ◽  
Planning And Control ◽  
Control Scheme ◽  
Active Research ◽  
And Control ◽  
Collaborative Robot

Human-Robot Interaction (HRI) for collaborative robots has become an active research topic recently. Collaborative robots assist the human workers in their tasks and improve their efficiency. But the worker should also feel safe and comfortable while interacting with the robot. In this paper, we propose a human-following motion planning and control scheme for a collaborative robot which supplies the necessary parts and tools to a worker in an assembly process in a factory. In our proposed scheme, a 3-D sensing system is employed to measure the skeletal data of the worker. At each sampling time of the sensing system, an optimal delivery position is estimated using the real-time worker data. At the same time, the future positions of the worker are predicted as probabilistic distributions. A Model Predictive Control (MPC) based trajectory planner is used to calculate a robot trajectory that supplies the required parts and tools to the worker and follows the predicted future positions of the worker. We have installed our proposed scheme in a collaborative robot system with a 2-DOF planar manipulator. Experimental results show that the proposed scheme enables the robot to provide anytime assistance to a worker who is moving around in the workspace while ensuring the safety and comfort of the worker.

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