There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

This paper studies practical tracking control design of robot manipulators with continuous fractional-order nonsingular terminal sliding mode (CFONTSM) based on time-delay estimation (TDE). The proposed control design requires no detailed information about the robot dynamics, leading to an attractive model-free nature thanks to TDE, and ensures fast convergence and high tracking precision under heavy lumped uncertainties due to the FONTSM surface and fast-TSM-type reaching law. Stability of the closed-loop system and finite-time convergence are analyzed using Lyapunov stability theory. Comparative 2-DOF (degree of freedom) simulation and experiment results show that the proposed control design can ensure higher tracking precision and faster convergence compared with TDE-based continuous integer-order NTSM (CIONTSM) design in a wide range of speed; meanwhile, better performance is also observed compared with TDE-based IONTSM and FONTSM control designs using a boundary layer technique.

Practical Tracking Control of Robot Manipulators With Continuous Fractional-Order Nonsingular Terminal Sliding Mode

https://www.mdpi.com/2218-6581/5/2/11/pdf

State of the Art Robotic Grippers and Applications

Underactuated robotics is an emerging research direction in the field of robotics. The control input of the underactuated robot is less than the degree of freedom of the system. It has the advantag...

https://journals.sagepub.com/doi/pdf/10.1177/1729881419862164

Underactuated robotics: A review:

This paper reports the development of an intelligent shared control system for a robotic manipulator that is commanded by the user's mind. The target objects are detected by a vision system and then displayed to the user in a video that shows them fused with flicking diamonds that are designed to excite electroencephalograph (EEG) signals at different frequency bands. Through the analysis of the invoked EEG signals, a brain–computer interface is developed to infer the exact object that is required by the user. These results are then transferred to the shared control system, which is enabled by visual servoing techniques to achieve accurate object manipulation. The task motion and self-motion (CTS) methods are coordinated to enhance the intelligence of the shared control system by equipping the robot with an autonomous obstacle avoidance function. Extensive experimental studies are performed to verify that the adaptive object tracking algorithm, the CTS method, and the least-squares method are helpful in improving the performance of the intelligent robotic system.

Mind Control of a Robotic Arm With Visual Fusion Technology

This paper presents an online image-based visual servoing (IBVS) controller for a 6-degrees-of-freedom (DOF) robotic system based on the robust model predictive control (RMPC) method. The controller is designed considering the robotic visual servoing system’s input and output constraints, such as robot physical limitations and visibility constraints. The proposed IBVS controller avoids the inverse of the image Jacobian matrix and hence can solve the intractable problems for the classical IBVS controller, such as large displacements between the initial and the desired positions of the camera. To verify the effectiveness of the proposed algorithm, real-time experimental results on a 6-DOF robot manipulator with eye-in-hand configuration are presented and discussed.

Robust Online Model Predictive Control for a Constrained Image-Based Visual Servoing

The ball and beam system is a laboratory equipment with high nonlinearity in its dynamics The aims of this research are to model the ball and beam system considering nonlinear factors and coupling effect and to design controllers to control the ball position The LQR is designed considering two Degrees-of-Freedom and coupling dynamics The parameters of the LQR are tuned using Genetic Algorithm (GA) Jacobian linearization method is used to linearize the system around operating-point Due to the noise of the sensor in the experimental setup, a state observer is designed to observe the velocity of the ball In order to compare the performance of the LQR and study the effect of simplifying assumptions, two control strategies are designed and implemented: Proportional Derivative Integral (PID) as non-model based control strategy, hybrid PID and Linear Quadratic Regulator (LQR) as combination of model based and non-model based control strategies The experimental results of this research prove the model based control strategies outperforms the non-model based or hybrid controllers in a nonlinear and noisy ball and beam system In addition, it is shown that the coupling dynamics cannot be eliminated as a simplifying assumption in designing the controller

Modeling and control of ball and beam system using model based and non-model based control approaches

This paper presents a new image-based visual servoing (IBVS) controller named augmented IBVS for a 6-DOF manipulator. The main idea of this controller is that it produces acceleration as the controlling command. A proportional-derivative controller is developed to provide the robot with the controlling command. This controller can achieve a smoother and more linear feature trajectory in the image space and decrease the risk that the features leave the field of view. The developed control method also enhances the camera trajectory in 3-D space. The stability of the proposed method is fully investigated by using the Lyapunov method and the perturbed systems theory. Experimental tests are performed on a 6-DOF robotic system to validate the effectiveness of the proposed controller. The performance of the controller is compared with that of a conventional IBVS.

Augmented Image-Based Visual Servoing of a Manipulator Using Acceleration Command

Trajectory planning is a useful technique in robotics for guiding the robot through complicated tasks. In this paper, a new semi-offline trajectory planning method is developed to perform image-based visual servoing (IBVS) tasks for a 6 DOFs robotic manipulator system. This method extends the operation range of the system compared with the traditional IBVS controllers. In this method, the camera's velocity screw is parametrized using time-based profiles. The parameters of the velocity profile are then determined by minimizing the cost function consisting of the error between the initial and desired features while respecting the system constraints. A depth-estimation algorithm is proposed to provide the trajectory planning algorithm with a good estimation of the initial depth. The algorithm for planning the orientation of the robot is decoupled from the position planning of the robot. This method eliminates the limitation caused by camera's field of view. The algorithm is validated via the experiment on a 6 DOFs Denso robot in an eye-in-hand configuration. The experimental results demonstrate that the proposed method can overcome some major IBVS drawbacks such as surpassing the system limits and causing instability of the system in fulfilling the tasks which require a 180° rotation of the camera about its center.

Image-Based Visual Servoing Using an Optimized Trajectory Planning Technique

In this paper a comparative analysis is represented on various navigation guidance methods used for intercepting fast maneuvering moving objects. A glancing revision is introduced on relevant works within the introduction section. Four common methods for navigation guidance known as PNG, APNG, IPNG and AIPNG are under investigation. Results demonstrate their infirmity on smoothly intercepting a moving object. Hence, to improve the navigation guidance methods and to adapt them with robotic problems a modified version of AIPNG is proposed for 2D problems and is developed for 3D problems utilization.

/pdf/performance-comparison-of-various-navigation-guidance-3jdei6xlbq.pdf

Performance comparison of various navigation guidance methods in interception of a moving object by a serial manipulator considering its kinematic and dynamic limits

Mohammad Keshmiri

Papers

Robust Online Model Predictive Control for a Constrained Image-Based Visual Servoing

Modeling and control of ball and beam system using model based and non-model based control approaches

Augmented Image-Based Visual Servoing of a Manipulator Using Acceleration Command

Image-Based Visual Servoing Using an Optimized Trajectory Planning Technique

Performance comparison of various navigation guidance methods in interception of a moving object by a serial manipulator considering its kinematic and dynamic limits