Remote Control of Mobile Robot using the Virtual Reality

In this paper we present the simulation and manipulation of  teleoperation system for remote control of mobile robot using the Virtual Reality (VR). The objective of this work is to allow the operator to control and supervise a unicycle type mobile robot. In this research we followed three ways: The use of articulated robotic mobile on the Web, the design of remote environment for the experimentation using the network for the mobile robot and the  architecture of control is proposed to facilitate the piloting of the robot. This work proposes a hardware and software architecture based on communication and information technologies to control the virtual robot to improve the control towards the remote robot. A path planning method is integrated to the remote control system. Results show the real possibilities offered by this manipulation, in order to follow a trajectory of the robot and to create applications with a distance access to facilities through networks like the Internet and wireless

Integral Backstepping Approach for Mobile Robot Control

This paper presents the trajectory tracking problem of a unicycle-type mobile robots. A robust output tracking controller for nonlinear systems in the presence of disturbances is proposed, the approach is based on the combination of integral action and Backstepping technique to compensate for the dynamic disturbances. For desired trajectory, the values of the linear and angular velocities of the robot are assured by the kinematic controller. The control law guarantees stability of the robot by using the lyapunov theorem. The simulation and experimental results are presented to verify the designed trajectory tracking control

A novel aerial manipulation design, modelling and control for geometric com compensation

International audienceThis paper presents the design and modelling of a new Aerial manipulating system, that resolve a displacement of centre of gravity of the whole system with a mechanical device. A prismatic joint between the multirotor and a robotic arm is introduced to make a centre of mass as close as to the geometric centre of the whole system. This paper details also the geometric and dynamic modelling of a coupled system with a Lagrange formalism and control law with a Closed Loop Inverse Kinematic Algorithm (CLIKA). This dynamic inverse control is validated in a Simulink environment showing the efficiency of our approach

A New Classification and Aerial Manipulation Q-PRR Design

International audienceThis paper presents a new designation and classification of system with UAV and robot manipulator where a new nomenclature is recognized as being the first contribution in the bibliography of design and systems. Several papers deal a problem of manipulation with a different unmanned aerial vehicle, robot arms and also with different naming of their systems, where the difficulty for locate and finding items and a good paper with its title or even by keywords, multirotor equipped with n-DoF robotic arm is the expression among the most widely used to describe that system. Aerial manipulation formula is presented and proved with a large example in the literature

Trajectory reconstruction for robot programming by demonstration

The reproduction of hand movements by a robot remains difficult and conventional learning methods do not allow us to faithfully recreate these movements because it is very difficult when the number of crossing points is very large. Programming by Demonstration gives a better opportunity for solving this problem by tracking the user’s movements with a motion capture system and creating a robotic program to reproduce the performed tasks. This paper presents a Programming by Demonstration system in a trajectory level for the reproduction of hand/tool movement by a manipulator robot; this was realized by tracking the user’s movement with the ArToolkit and reconstructing the trajectories by using the constrained cubic spline. The results obtained with the constrained cubic spline were compared with cubic spline interpolation. Finally the obtained trajectories have been simulated in a virtual environment on the Puma 600 robot

Echo state network‐based feature extraction for efficient color image segmentation

Image segmentation plays a crucial role in many image processing and understanding applications. Despite the huge number of proposed image segmentation techniques, accurate segmentation remains a significant challenge in image analysis. This article investigates the viability of using echo state network (ESN), a biologically inspired recurrent neural network, as features extractor for efficient color image segmentation. First, an ensemble of initial pixel features is extracted from the original images and injected into the ESN reservoir. Second, the internal activations of the reservoir neurons are used as new pixel features. Third, the new features are classified using a feed forward neural network as a readout layer for the ESN. The quality of the pixel features produced by the ESN is evaluated through extensive series of experiments conducted on real world image datasets. The optimal operating range of different ESN setup parameters for producing competitive quality features is identified. The performance of the proposed ESN‐based framework is also evaluated on a domain‐specific application, namely, blood vessel segmentation in retinal images where experiments are conducted on the widely used digital retinal images for vessel extraction (DRIVE) dataset. The obtained results demonstrate that the proposed method outperforms state‐of‐the‐art general segmentation techniques in terms of performance with an F‐score of 0.92 ± 0.003 on the segmentation evaluation dataset. In addition, the proposed method achieves a comparable segmentation accuracy (0.9470) comparing with reported techniques of segmentation of blood vessels in images of retina and outperform them in terms of processing time. The average time required by our technique to segment one retinal image from DRIVE dataset is 8 seconds. Furthermore, empirically derived guidelines are proposed for adequately setting the ESN parameters for effective color image segmentation

Adaptive Neuro-fuzzy Inference System Based Control of puma 600 Robot Manipulator

The strong dependence of the computed torque control of dynamic model of the robot manipulator makes this one very sensitive to uncertainties of modelling and to the external disturbances. In general, the vector of Coriolis torque, centrifugal and gravity is very complicated, consequently, very difficult to modelled. Fuzzy Logic Controller can very well describe the desired system behavior with simple “if-then” relations owing the designer to derive “if-then” rules manually by trial and error. On the other hand, Neural Networks perform function approximation of a system but cannot interpret the solution obtained neither check if its solution is plausible. The two approaches are complementary. Combining them, Neural Networks will allow learning capability while Fuzzy-Logic will bring knowledge representation (Neuro-Fuzzy). This paper presents the control of puma 600 robot arm using Adaptive Neuro Fuzzy Inference System (ANFIS) based computed torque controller (type PD). Numerical simulation using the dynamic model of puma 600 robot arm shows the effectiveness of the approach in improving the computed torque method. Comparative evaluation with Fuzzy computed torque (type PD) control is presented to validate the controller design. The results presented emphasize that a satisfactory trajectory tracking precision and stabilility could be achieved using ANFIS controller than Fuzzy controller. Keywords: Fuzzy computed torque control, Robot control, Adaptive neuro-fuzzy inference system (ANFIS).DOI:http://dx.doi.org/10.11591/ijece.v2i1.11

Design and Manipulation in Augmented Reality of Fanuc 200iC Robot

In this paper, an AR (Augmented reality) system based on a multimodal user interface is proposed and its core techniques are described. The objective of this work is to realize certain task that operators can use the virtual robot to ameliorate the interaction with the real world using AR environment. VC++ and OpenGL are used to create this application.AR applications (ARToolKit) is used to detect the real-time position and orientation of camera and to facilite the operator’s observation and operation. Experiments prove that the system is reliable and efficient. Simulation result is obtained and it is very useful for designers to ameliorate the interaction with the real world