Plasma sprayed titanium coatings with/without a shroud

Abstract: Titanium coatings were deposited by plasma spraying with and without a shroud. The titanium coatings were then assessed by scanning electron microscopy. A comparison in microstructure between titanium coatings with and without the shroud was carried out. The results showed that the shroud played an important role in protecting the titanium particles from oxidation. The presence of the shroud led to a reduction in coating porosity. The reduction in air entrainment with t he shroud resulted in better heating of the particles, and an enhanced microstructure with lower porosity in the shrouded titanium coatings were observed compared to the air plasma sprayed counterpart

Actuators and sensors for application in agricultural robots: A review

In recent years, with the rapid development of science and technology, agricultural robots have gradually begun to replace humans, to complete various agricultural operations, changing traditional agricultural production methods. Not only is the labor input reduced, but also the production efficiency can be improved, which invariably contributes to the development of smart agriculture. This paper reviews the core technologies used for agricultural robots in non-structural environments. In addition, we review the technological progress of drive systems, control strategies, end-effectors, robotic arms, environmental perception, and other related systems. This research shows that in a non-structured agricultural environment, using cameras and light detection and ranging (LiDAR), as well as ultrasonic and satellite navigation equipment, and by integrating sensing, transmission, control, and operation, different types of actuators can be innovatively designed and developed to drive the advance of agricultural robots, to meet the delicate and complex requirements of agricultural products as operational objects, such that better productivity and standardization of agriculture can be achieved. In summary, agricultural production is developing toward a data-driven, standardized, and unmanned approach, with smart agriculture supported by actuator-driven-based agricultural robots. This paper concludes with a summary of the main existing technologies and challenges in the development of actuators for applications in agricultural robots, and the outlook regarding the primary development directions of agricultural robots in the near future

Tactile Sensing with Accelerometers in Prehensile Grippers for Robots

This is the author’s version of a work that was accepted for publication in Mechatronics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Mechatronics, Vol. 33, (2016)] DOI 10.1016/j.mechatronics.2015.11.007.Several pneumatic grippers with accelerometers attached to their fingers have been developed and tested. The first gripper is able to classify the hardness of different cylinders, estimate the pneumatic pressure, monitor the position and speed of the gripper fingers, and study the phases of the action of grasping and the influence of the relative position between the gripper and the cylinders. The other grippers manipulate and assess the firmness of eggplants and mangoes. To achieve a gentle manipulation, the grippers employ fingers with several degrees of freedom in different configurations and have a membrane filled with a fluid that allows their hardness to be controlled by means of the jamming transition of the granular fluid inside it. To assess the firmness of eggplants and mangoes and avoid the influence of the relative position between product and gripper, the firmness is estimated while the products are being held by the fingers. Better performance of the accelerometers is achieved when the finger employs the granular fluid. The article presents methods for designing grippers capable of assessing the firmness of irregular products with accelerometers. At the same time, it also studies the possibilities that accelerometers, attached to different pneumatic robot gripper fingers, offer as tactile sensors. (C) 2015 Elsevier Ltd. All rights reserved.This research is supported by the MANI-DACSA project (Grant number RTA2012-00062-C04-02), which is partially funded by the Spanish Government (Ministerio de Economia y Competitividad.).Blanes Campos, C.; Mellado Arteche, M.; Beltrán Beltrán, P. (2016). Tactile Sensing with Accelerometers in Prehensile Grippers for Robots. Mechatronics. 33:1-12. https://doi.org/10.1016/j.mechatronics.2015.11.007S1123

Development of a SMA-fishing-line-McKibben bending actuator

High power-to-weight ratio soft artificial muscles are of overarching importance to enable inherently safer solutions to human-robot interactions. Traditional air driven soft McKibben artificial muscles are linear actuators. It is impossible for them to realize bending motions through a single McKibben muscle. Over two McKibben muscles should normally be used to achieve bending or rotational motions, leading to heavier and larger systems. In addition, air driven McKibben muscles are highly nonlinear in nature, making them difficult to be controlled precisely. A SMA(shape memory alloy)–fishing–line–McKibben (SFLM) bending actuator has been developed. This novel artificial actuator, made of a SMA-fishing-line muscle and a McKibben muscle, was able to produce the maximum output force of 3.0 N and the maximum bending angle (the rotation of the end face) of 61°. This may promote the application of individual McKibben muscles or SMA-fishing-line muscles alone. An output force control method for SFLM is proposed, and based on MATLAB/Simulink software the experiment platform is set up, the effectiveness of control system is verified through output force experiments. A three-fingered SFLM gripper driven by three SFLMs has been designed for a case study, which the maximum carrying capacity is 650.4 ± 0.2 g

DESIGN OF THREE FINGER GRIPPER WITH FSR

Technological advancement is widening up by the advent of new inventions. Robots are going to be an integral part of the completely automated industries. There are many instances where profile detection. In this paper, discussed about the three finger gripper has the abilities with this dexterous electric gripper. Three fingers gripper is extreme changeability and fixable gripping control. Its finger has several positions of geometrics and dimensions. Its specific control of crossing point allows orthodox forward motion on the finger location, rapidity and force. These fingers design in CREO 3.0 software and produced by RPT. Fingers are evaluated to check if the finger is flexible motion. The force is measured by a force sensitive resister (FSR). A force sensor is measure a grasping object whose confrontation difference between before and after force is applied. The Arduino mega controller is used for controlling the servo motor and FSR in gripping motion. This servo motor is 180Ëšrotation angle, Control loop response mechanism is extensively used for accurate control. The Controlled gripper finger is sensed and gripped with force which is being analyzed in the data

Flexible Gripper, Design and Control for Soft Robotics

This paper presents the 3D design of a flexible gripper used for gripping polyform objects that require a certain degree of adaptation of the effector for its manipulation. For this case, the 3D printing of the gripper and its construction is exposed, where a fuzzy controller is implemented for its manipulation. The effector has a flexo resistance that provides information of the deflection of the gripper, this information and the desired grip force are part of the fuzzy controller that seeks to regulate the current of the servomotors that make up the structure of the gripper and are responsible for ensuring the grip. An efficient system is obtained for gripping polyform objects involving deflection of up to 5 mm with a current close to 112 mA

Bending angle prediction and control of soft pneumatic actuators with embedded flex sensors - a data-driven approach

In this paper, a purely data-driven modelling approach is presented for predicting and controlling the free bending angle response of a typical soft pneumatic actuator (SPA), embedded with a resistive flex sensor. An experimental setup was constructed to test the SPA at different input pressure values and orientations, while recording the resulting feedback from the embedded flex sensor and on-board pressure sensor. A calibrated high speed camera captures image frames during the actuation, which are then analysed using an image processing program to calculate the actual bending angle and synchronise it with the recorded sensory feedback. Empirical models were derived based on the generated experimental data using two common data-driven modelling techniques; regression analysis and artificial neural networks. Both techniques were validated using a new dataset at untrained operating conditions to evaluate their prediction accuracy. Furthermore, the derived empirical model was used as part of a closed-loop PID controller to estimate and control the bending angle of the tested SPA based on the real-time sensory feedback generated. The tuned PID controller allowed the bending SPA to accurately follow stepped and sinusoidal reference signals, even in the presence of pressure leaks in the pneumatic supply. This work demonstrates how purely data-driven models can be effectively used in controlling the bending of SPAs under different operating conditions, avoiding the need for complex analytical modelling and material characterisation. Ultimately, the aim is to create more controllable soft grippers based on such SPAs with embedded sensing capabilities, to be used in applications requiring both a ‘soft touch’ as well as a more controllable object manipulation

Bending angle prediction and control of soft pneumatic actuators with embedded flex sensors: a data-driven approach

In this paper, a purely data-driven modelling approach is presented for predicting and controlling the free bending angle response of a typical soft pneumatic actuator (SPA), embedded with a resistive flex sensor. An experimental setup was constructed to test the SPA at different input pressure values and orientations, while recording the resulting feedback from the embedded flex sensor and on-board pressure sensor. A calibrated high speed camera captures image frames during the actuation, which are then analysed using an image processing program to calculate the actual bending angle and synchronise it with the recorded sensory feedback. Empirical models were derived based on the generated experimental data using two common data-driven modelling techniques; regression analysis and artificial neural networks. Both techniques were validated using a new dataset at untrained operating conditions to evaluate their prediction accuracy. Furthermore, the derived empirical model was used as part of a closed-loop PID controller to estimate and control the bending angle of the tested SPA based on the real-time sensory feedback generated. The tuned PID controller allowed the bending SPA to accurately follow stepped and sinusoidal reference signals, even in the presence of pressure leaks in the pneumatic supply. This work demonstrates how purely data-driven models can be effectively used in controlling the bending of SPAs under different operating conditions, avoiding the need for complex analytical modelling and material characterisation. Ultimately, the aim is to create more controllable soft grippers based on such SPAs with embedded sensing capabilities, to be used in applications requiring both a ‘soft touch’ as well as a more controllable object manipulation

Safe Grasping with a Force Controlled Soft Robotic Hand

Safe yet stable grasping requires a robotic hand to apply sufficient force on the object to immobilize it while keeping it from getting damaged. Soft robotic hands have been proposed for safe grasping due to their passive compliance, but even such a hand can crush objects if the applied force is too high. Thus for safe grasping, regulating the grasping force is of uttermost importance even with soft hands. In this work, we present a force controlled soft hand and use it to achieve safe grasping. To this end, resistive force and bend sensors are integrated in a soft hand, and a data-driven calibration method is proposed to estimate contact interaction forces. Given the force readings, the pneumatic pressures are regulated using a proportional-integral controller to achieve desired force. The controller is experimentally evaluated and benchmarked by grasping easily deformable objects such as plastic and paper cups without neither dropping nor deforming them. Together, the results demonstrate that our force controlled soft hand can grasp deformable objects in a safe yet stable manner.Comment: Accepted to 2020 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2020