Artificial intelligence systems are usually implemented either using machine learning or expert systems. Machine learning methods are usually more accurate and applicable to a broader range of applications. Expert sys...
Artificial intelligence systems are usually implemented either using machine learning or expert systems. Machine learning methods are usually more accurate and applicable to a broader range of applications. Expert systems, on the other hand, require much less data for training and generate more comprehensible results. These characteristics are typically desired in the fields of surgery and medicine because there isn't much data available. In order to give a machine's decisions a deeper level of semantics, it is also advantageous to incorporate a doctor's expertise into it. Furthermore, it is safer to understand the reasoning behind a machine's choices. In this paper, a Dempster-Shafer Theory (DST) based expert system is suggested for the task of surgical training skill assessment. An interval-based probabilistic feature analysis was applied to the data to assign values to the mass functions. Zhang's rule of combination was applied to handle the conflicting evidence in the prediction phase. The performance of the proposed method was compared to another DST classifier, SVM, and XGBoost. Our method outperforms SVM and other DST classifiers, but it is not as precise as XGBoost. By reducing the size of the dataset, the added benefit of using an expert system as opposed to a machine learning method was explored further. The performance of the suggested method is not adversely affected by the size of the dataset, whereas the XGBoost classifier is.
The efficient operation of large-scale Cable-Driven Parallel Robots (CDPRs) relies on precise calibration of kinematic parameters and the simplicity of the calibration process. This paper presents a graph-based self-c...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
The efficient operation of large-scale Cable-Driven Parallel Robots (CDPRs) relies on precise calibration of kinematic parameters and the simplicity of the calibration process. This paper presents a graph-based self-calibration framework that explicitly addresses cable sag effects and facilitates the calibration procedure for large-scale CDPRs by only relying on internal sensors. A unified factor graph is proposed, incorporating a catenary cable model to capture cable sagging. The factor graph iteratively refines kinematic parameters, including anchor point locations and initial cable length, by considering jointly onboard sensor data and the robot’s kineto-static model. The applicability and accuracy of the proposed technique are demonstrated through Finite Element (FE) simulations, on both large and small-scale CDPRs subjected to significant initialization perturbations.
In the paper, the model and prototype of the AC stabilizer have been developed based on the AVR ATmega328P microcontroller. The block diagram of the device, the electronic circuit and the algorithms of the system oper...
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ISBN:
(纸本)9798350334326
In the paper, the model and prototype of the AC stabilizer have been developed based on the AVR ATmega328P microcontroller. The block diagram of the device, the electronic circuit and the algorithms of the system operation have been developed. In particular, the algorithm includes software in C in the Arduino IDE. The AC voltage stabilizer is designed using the modular principle, which makes it possible to quickly upgrade. The AC voltage stabilizer makes it possible to maintain the supply voltage on the load within acceptable limits with significant deviations, has the ability to adjust the voltage range of the network to operate the stabilizer, manual adjustment potentiometers.
In the problem of simultaneously localization and mapping (SLAM) for a mobile robot, it is required to detect previously visited locations so the estimation error shall be reduced. Sensor observations are compared by ...
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ISBN:
(纸本)9781467372350
In the problem of simultaneously localization and mapping (SLAM) for a mobile robot, it is required to detect previously visited locations so the estimation error shall be reduced. Sensor observations are compared by a similarity metric to detect loops. In long term navigation or exploration, the number of observations increases and so the complexity of the loop closure detection. Several techniques are proposed in order to reduce the complexity of loop closure detection. Few algorithms have considered the loop closure detection from a subset of sensor observations. In this paper, the compressed sensing approach is exploited to detect loops from few sensor measurements. In the basic compressed sensing it is assumed that a signal has a sparse representation is a basis which means that only a few elements of the signal are non-zero. Based on the compressed sensing approach a sparse signal can be recovered from few linear noisy projections by l_1 minimization. The difference matrix which is widely used for loop detection has a sparse structure, where similar observations are shown by zero distance and different locations are indicated by ones. Based on the multiple measurement vector technique which is an extension of the basic compressed sensing, the loop closure detection is performed by comparison of few sensor observations. The applicability of the proposed algorithm is investigated in some outdoor environments through some publicly available data sets. It has been shown by some experiments that the proposed method can detect loops effectively.
This paper addresses a new method for navigation in dynamic environment. The proposed method is based on force field method and it is supposed that the robot performs SLAM and autonomous navigation in dynamic environm...
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This paper addresses a new method for navigation in dynamic environment. The proposed method is based on force field method and it is supposed that the robot performs SLAM and autonomous navigation in dynamic environment without any predefined information about dynamic obstacles. The movement of dynamic obstacles is predicted by Kalman filter and is used for collision detection purpose. In the time of collision detection, a modifying force is added to repulsive and attractive forces corresponding to the static environment and leads robot to avoid collision. Moreover, a safe turning angle is defined to assure safe navigation of the robot. The performance of proposed method, named Escaping Algorithm, is verified through different simulation and experimental tests. The results show the proper performance of Escaping Algorithm in term of dynamic obstacle avoidance as a practical method for autonomous navigation.
This paper presents a nonlinear controller for visual servoing system. Pose estimation is one of the fundamental issues in position-based visual servoing (PBVS) approach. A few researches have focused on controller sy...
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This paper presents a nonlinear controller for visual servoing system. Pose estimation is one of the fundamental issues in position-based visual servoing (PBVS) approach. A few researches have focused on controller synthesis under modeling uncertainty and measurement noise of estimated position. In this research, PD-type sliding surface is designed for tracking target. The control signal is obtained from the sliding surface and the stability of the algorithm is verified by Lyapunov theory. Moreover, a recent designed robust estimator based on unscented Kalman observer (UKO) cascading with Kalman filter (KF) is used to estimate the pose, velocity and acceleration of the target. The combination of the implemented estimator and the proposed controller provide a stable and robust structure in PBVS. The reported experimental results, verify the effectiveness of the proposed method in an industrial visual servoing system.
The problem of unsupervised classification of 3D objects from depth information is investigated in this paper. The range images are represented efficiently as sensor observations. Considering the high-dimensionality o...
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The problem of unsupervised classification of 3D objects from depth information is investigated in this paper. The range images are represented efficiently as sensor observations. Considering the high-dimensionality of 3D object classification, little attention has been paid to the curse of dimensionality in the existing state-of-the-art algorithms. In order to remedy this problem, a low-dimensional representation is defined here. The sparse model of every range image is constructed from a parametric dictionary. Employing the algorithmic information theory, a universal normalized metric is used for comparison of Kolmogorov complexity based representations of sparse models. Finally, most similar objects are grouped together. Experimental results show efficiency and accuracy of the proposed method in comparison to a recently proposed method.
Visual Servoing is generally comprised of feature tracking and control. According to the literature, no attempt has already been made to optimize these two parts together. In kernel based visual servoing method, the m...
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Visual Servoing is generally comprised of feature tracking and control. According to the literature, no attempt has already been made to optimize these two parts together. In kernel based visual servoing method, the main objective is to combine and optimize the entire control loop. By kernel definition, a Lyapanov candidate function is formed and the control input is computed so that the Lyapanov stability can be verified. This is performed in four degrees of freedom. In the present study, previous kernel algorithm from the recorded literature has been implemented. We have used the KBVS for our purpose such that an object without any marker is tracked. This method is chosen because of its robustness, speed and featureless properties. Furthermore, in order to show the visual tracking performance, all four degrees of freedom have been synthesized. Experimental results verifies the effectiveness of this method implemented for four degrees of freedom movements.
In this paper robust PID control of fully-constrained cable-driven robots with elastic cables is studied in detail. To develop the idea, a robust PID control for cable-driven robots with ideal rigid cables is firstly ...
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In this paper robust PID control of fully-constrained cable-driven robots with elastic cables is studied in detail. To develop the idea, a robust PID control for cable-driven robots with ideal rigid cables is firstly designed and then, this controller is extended for the robots with elastic cables. To overcome vibrations caused by inevitable elasticity of cables, a composite control law is proposed based on singular perturbation theory. The proposed control algorithm includes robust PID control for corresponding rigid model and a corrective term. Using the proposed control algorithm the dynamics of the cable-driven robot is divided into slow and fast subsystems. Then, based on the results of singular perturbation theory, stability analysis of the total system is performed. Finally, the effectiveness of the proposed control law is investigated through several simulations on a planar cable-driven robot.
In this paper design and control of planar cable-driven parallel robots are studied in an experimental prospective. Since in this class of manipulators, cable tensionability conditions must be met, feedback control of...
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In this paper design and control of planar cable-driven parallel robots are studied in an experimental prospective. Since in this class of manipulators, cable tensionability conditions must be met, feedback control of such robots becomes more challenging than for conventional robots. To meet these conditions, internal force control structure is introduced and used in addition to a PID control scheme to ensure that all cables remain in tension. A robust PID controller is proposed for partial knowledge of the robot, to keep the tracking errors bounded. Finally, the effectiveness of the proposed control algorithm is examined through experiments on K.N. Toosi planar cable-driven robot and it is shown that the proposed control structure is able to provide suitable performance in practice.
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