Design, Implementation, and Validation of Robust Fractional-Order PD Controller for Wheeled Mobile Robot Trajectory Tracking

Zhang, Lichuan; Liu, Lu; Zhang, Shuo

doi:10.1155/2020/9523549

Cited by 12 publications

(6 citation statements)

References 40 publications

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“…Each type of this robot moving technique has several advantages and limitations. The main feature of the wheeled mobile robots is the high velocity [21]- [23], while both snake and worm robots consider more suitable for narrow paths [24]. A soft floor is the primary work area for sphere-shaped machine [25], [26].…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Soft Mobile Robot Inspired by Silkworm Body and Movement Behavior

Abed,

Al-Ibadi,

Abed

2023

Journal of Robotics and Control

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Designing an inexpensive, low-noise, safe for individual, mobile robot with an efficient vision system represents a challenge. This paper proposes a soft mobile robot inspired by the silkworm body structure and moving behavior. Two identical pneumatic artificial muscles (PAM) have been used to design the body of the robot by sewing the PAMs longitudinally. The proposed robot moves forward, left, and right in steps depending on the relative contraction ratio of the actuators. The connection between the two artificial muscles gives the steering performance at different air pressures of each PAM. A camera (eye) integrated into the proposed soft robot helps it to control its motion and direction. The silkworm soft robot detects a specific object and tracks it continuously. The proposed vision system is used to help with automatic tracking based on deep learning platforms with real-time live IR camera. The object detection platform, named, YOLOv3 is used effectively to solve the challenge of detecting high-speed tiny objects like Tennis balls. The model is trained with a dataset consisting of images of Tennis balls. The work is simulated with Google Colab and then tested in real-time on an embedded device mated with a fast GPU called Jetson Nano development kit. The presented object follower robot is cheap, fast-tracking, and friendly to the environment. The system reaches a 99% accuracy rate during training and testing. Validation results are obtained and recorded to prove the effectiveness of this novel silkworm soft robot. The research contribution is designing and implementing a soft mobile robot with an effective vision system.

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Section: Introductionmentioning

confidence: 99%

Vision-Based Soft Mobile Robot Inspired by Silkworm Body and Movement Behavior

Abed,

Al-Ibadi,

Abed

2023

Journal of Robotics and Control

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show abstract

“…To research these problems, researchers have proposed many methods all over the world. FOPD (Robust Fractional-Order PD) Controller is researched for a Wheeled Mobile Robot (WMR) in reference [6], which firstly presents an improved flat phase property as a robust controller tuning specification to improve the controlled system robustness while this reference just considers how to guarantee the stability of the system and the tracking error is very large. To stabilize the translational and rotational motion of a quadrotor system and enforce it to track a given trajectory with minimum energy and error, a NLPID (nonlinear proportional integral derivative) controller is proposed in reference [7], where their parameters are tuned using a genetic algorithm (GA) to minimize a multiobjective output performance index.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Trajectory Tracking Algorithm of a Quadrotor with Sliding Mode Control and Multilayer Neural Network

et al. 2022

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To improve the trajectory tracking accuracy, the anti-jamming performance, and the environment adaptability of a quadrotor, the paper proposes a new adaptive trajectory tracking algorithm with multilayer neural network and sliding mode control method. The major difference between other related approaches is that the paper uses the multilayer neural network in the system and the neural network is online computing in the whole process. Firstly, the paper establishes the quadrotor dynamic model and introduces the conception of Sigma-Pi neural network. Then, the paper adds the neural network to the attitude and trajectory tracking control loop. Moreover, the paper designs the adaptive neural network control law. At last, to illustrate the stability of the adaptive control law, the paper gives the Lyapunov stability analysis. Finally, to demonstrate the effectiveness of the method, the paper gives different types of simulation. Comparing with different cases, when increasing the layer of the neural network, the trajectory tracking performance becomes better. In addition, introducing multilayer neural network into the system could improve the anti-interference ability of the system and has a high-precision in tracking the desire trajectory.

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“…Each type of robot moving technique has several advantages and limitations. The main feature of the wheeled mobile robots is the high velocity [10,11], while both snake and worm robots are considered more suitable for narrow paths [12]. A smooth floor is the main work area for spherical robots [13,14].…”

Section: Introductionmentioning

confidence: 99%

“…Robots that have been made of rigid materials are heavy, unsafe for individuals, expensive, require a wide workspace, and they do not have the ability to adapt to the environment [11,16,17]. Applications can be selected for each type of moving robot depending on the structure, materials, and environment.…”

Section: Introductionmentioning

confidence: 99%

An Automatic Self Shape-Shifting Soft Mobile Robot (A4SMR)

2022

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This article proposes a mobile robot that is fully constructed and actuated by utilising a pneumatic artificial muscle (PAM). Several features are shown in this design including softness, lightweight, and shape change. The robot that has been designed in this article is constructed with four identical contraction actuators: one pair for steering and moving forward and the second pair for shape-shifting. The proposed mobile robot has the ability to move forward, steer, and shapeshift to navigate through narrow paths. The kinematic for the system is provided for the area of the robot by using the shoelace formula by utilising a Pixy camera to track the coordinates of the four vertices.

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Design, Implementation, and Validation of Robust Fractional-Order PD Controller for Wheeled Mobile Robot Trajectory Tracking

Cited by 12 publications

References 40 publications

Vision-Based Soft Mobile Robot Inspired by Silkworm Body and Movement Behavior

Vision-Based Soft Mobile Robot Inspired by Silkworm Body and Movement Behavior

Adaptive Trajectory Tracking Algorithm of a Quadrotor with Sliding Mode Control and Multilayer Neural Network

An Automatic Self Shape-Shifting Soft Mobile Robot (A4SMR)

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