In this paper, motion control of wheeled mobile Robots (WMR) based object oriented method by using Delphi 4.0 programming language is presented A software package to enhance wheeled mobile Robots' capability and efficiency is developed In this development, all parts of WMR's such as motors, sensors, driver, etc. are considered separately. A software environment has been created to present a suitable setting for Robot programming by using personal computers. Finally, a three DOF mobile Robot is tested with output data's of the ware.

This paper presents an example of how a differential pressure sensor can be used to improve grasping of in-mold-labelling (IML) Robots. In order to minimize mold-open time on injection molding machines, shorter operation time is desirable. To achieve this goal, an analysis of grasping labels using the in-mold-labelling Robots was done with different approaches to improving the grasping process by measuring pressure in the chambers of the cylinder which carries the tool for grasping labels. The approach that uses the differential pressure sensor has proved best.

In this study, novel robust impedance control for lower-limb rehabilitation Robotic system using voltage control strategy is used. Most existing control approaches are based on control torque strategy, which requires knowledge of Robot dynamics as well as dynamics of patients. This obliges the controller to overcome complex problems such as uncertainty and nonlinearity involved in the dynamics of the system, Robot and patients. Conversely, the voltage-based control approaches are free from the system dynamics. In addition, it considers the actuator dynamics. The performance of voltage-based approaches is demonstrated by experimental result in Robotic applications. Compared with torque control scheme, it is simpler, less computational and more efficient. Nevertheless, uncertainty of actuator dynamics results in challenges for the voltage control strategy applications. The present paper presents novel robust impedance control based on the voltage control strategy. To overcome uncertainties, the adaptive fuzzy estimator is designed based on the voltage-based strategy. The proposed control is verified by stability analysis. To illustrate the effectiveness of the control approach, 1-DOF lower-limb rehabilitation Robot is designed. Both torque-based impedance control and the voltage-based impedance control are compared through therapeutic exercise. It is shown that the voltage-based impedance control performs better than the traditional torque-based impedance control. Simulation and experimental results both show that the proposed voltage-based robust impedance control is superior to voltage-based impedance control in presence of uncertainties.

Exoskeleton Robot has attracted attention of many researchers because it realizes an old aspiration to attain a machine which is worn by man and maximizes his might via its powerful actuators. Thorough coordination between Robot movements and that of user constitutes the greatest complexity of exoskeleton technology. Investigations showed that impedance control (IC) is suitable for this application but the present forms of IC are mostly dedicated to industrial Robots which have significant differences with exoskeleton. In this article a versatile form of IC for the mentioned application is developed. Besides, according to perpetual uncertainties in load and measured force signals, for the first time an adaptive method for IC of exoskeleton Robot is implemented. Simulating operation of Robot in tracking user's walking motion while carrying a load of 50 (Kg) and with uncertainties in load and measured forces, proves efficiency of the proposed control method. Tracking error during simulation is almost zero and torques needed at interfaces are immaterial.

The suspension system of a vehicle is one of the most important parts which is involved in the process of vehicle designing. When a vehicle suspension system is designed, the evaluation of its performance against the road disturbances such as shocks and bumps are very important. The most commonly used systems consist of four hydraulic Jacks with mobility in vertical line with low speed and low exactitude. This paper offers a new mechanism for inspecting the suspension system of a vehicle using a parallel Robot called Stewart. This Robot is a special kind of parallel Robots with capability of movements in different directions with high speed, accuracy and repeatability. In this paper the suspension system is evaluated on a quarter model of a simulated vehicle with control and guidance of Stewart Robot using PID controller. The Stewart Robot simulates the isolated and uneven bumps on a flat road in order to evaluate the given suspension system, and to investigate some criteria such as comforting of the passengers and remaining of the vehicle on the road. The results of the simulations show that the proposed method has a high accuracy, applicability and flexibility as well as simplicity, compared to currently used mechanisms.

Background and Objectives: Signage is everywhere, and a Robot should be able to take advantage of signs to help it localize (including Visual Place Recognition (VPR)) and map. Robust text detection & recognition in the wild is challenging due to pose, irregular text instances, illumination variations, viewpoint changes, and occlusion factors.Methods: This paper proposes an end-to-end scene text spotting model that simultaneously outputs the text string and bounding boxes. The proposed model leverages a pre-trained Vision Transformer based (ViT) architecture combined with a multi-task transformer-based text detector more suitable for the VPR task. Our central contribution is introducing an end-to-end scene text spotting framework to adequately capture the irregular and occluded text regions in different challenging places. We first equip the ViT backbone using a masked autoencoder (MAE) to capture partially occluded characters to address the occlusion problem. Then, we use a multi-task prediction head for the proposed model to handle arbitrary shapes of text instances with polygon bounding boxes.Results: The evaluation of the proposed architecture's performance for VPR involved conducting several experiments on the challenging Self-Collected Text Place (SCTP) benchmark dataset. The well-known evaluation metric, Precision-Recall, was employed to measure the performance of the proposed pipeline. The final model achieved the following performances, Recall = 0.93 and Precision = 0.8, upon testing on this benchmark.Conclusion: The initial experimental results show that the proposed model outperforms the state-of-the-art (SOTA) methods in comparison to the SCTP dataset, which confirms the robustness of the proposed end-to-end scene text detection and recognition model.