At present, many literatures have studied the control of manipulator, various control approaches that attenuate the effect of robotic uncertainties have been proposed, such as fuzzy control, robust adaptive control, sliding mode control, and neural network control. Literature [1-3] shows the robust control of the mechanicalarm can guarantee the overall stability of the system, but it affects the real-time engineering application. Literature [4-8] used the universal approximation feature of the fuzzy system to realize the approximation of the uncertainty; Fuzzy approximation is a better way to deal with uncertainty. The more the precision of fuzzy approximation is, the more fuzzy rules are, Therefore, the problem of high dimension of fuzzy system is very widespread.
The mechanicalarm suitable for the curtain wall installation should include at least the following functions: free displacement, three-dimensional regulation and grab and lift. The technology of the mechanicalarm is researched with the aid of the structural calculation results by the professional devices . First, the project department conducts the field survey and measurement and completes the feasibility analysis . Then the mechanicalarm is developed and produced, and finally the improvement and technical summary are made .
Robotic arm is the type of mechanicalarm which is fixed to the receiver part of the circuit; the control signal came from the Arduino output based on the gesture input given in the transmitter part by using accelerometer sensor. The robotic arm can rotate about the axis of 360 degree, which is fixed to the one of the DC geared motor. The rotational control and the movement of the arm is based on the gesture input that is given from the transmitter section. The one part of hand is about 20 cm and another part of the arm (elbow part) which is 30 cm long. The certain load is applied at the end of the arm for lifting the objects of desired weight. The servo motor is used for the purpose of gripping and placing the objects, because the servo motor is used for the low torque application. The control of the gripper is from the flex sensor which is in the transmitter part. That voltage output is sent to the Arduino which processes that signal and given to the nRF transmitter. The robotic arm will be controlled via the designed controller and it will be able to grab, pick up and move objects according to their weights and shape. The manipulator design is mostly expected to pick up cubes and the geometric shapes like a box.
An attempt has been made to add value to machine production automating repetitive tasks that could be done by automatic arms on the X-Y table. So we have arranged some kind of machinery regarding our aim will be fulfilled. At working conditions of the machine, workpiece handling is a difficult task for the worker especially in removing the workpiece from the die after machining. The paper proposes a cheap and effective method for the design and manufacturing of a three degree of freedom in a pneumatic way for the robotic arm. With this proposed approach the sequential design intents are captured, organized and implemented based on the entire system objectives, as opposed to the conventional design process which aims at individual components optimization. By considering the mechanical arm’s performance objectives, the design starts with modelling the integration of all the individual links constituting the manipulator. As a result, the proposed approach for manipulator design yields substantially less number of iterations, automatic propagation of design changes and the great saving of design efforts. Further with the best machining process and cheapest material, catering the strength and machining requirements suitable materials are selected to fulfill the objective. Keywords: Air compressor, Air, Air regulator, Arms, Cylinder clamps, Gripper, Pneumatic cylinders
In this paper, the robot is equipped with camera, temperature sensor, humidity sensor and smoke sensor, whose mechanicalarm is 6 degrees of freedom, left hand is a bionic mechanical claw and the right is a mechanical clip . Robotic walking system is wheeled structure.
Therefore, in order to guarantee outstanding performance, Audi AG (Ingolstadt, Germany) and GEFASOFT GmbH (Regensburg, Germany) jointly developed a calibration routine including complex software. The goal of this effort was to provide a mechanical set up, based on CCD cameras, which can be used in-line during auto assembly. GEFASOFT took part in the software development for the CCD camera and the image processing tools, while other system partners developed the mechanicalarm.
bridge (FB) SM based MMC , the alternate-arm multilevel converter , the clamped double SM based MMC , the cross-connected SM based MMC , and the hybrid MMC [20, 21], have been proposed. Each can block DC faults immediately by blocking all of the switching devices. However, all of these approaches require additional semiconductor devices in the conduction path, resulting in higher power loss and capital cost than the equivalent HB-MMC. In addition, these configurations can only prevent over-current in the converters themselves, and cannot isolate the fault from the healthy network in the HVDC system. DC switches are still required to disconnect the faulted branch so that the healthy parts of the network can be restarted: all converter stations must be shut down prior to fault isolation by the DC switches . Consequently, solid-state or hybrid DCCBs are still required to quickly isolate the fault and avoid the shutdown of the entire system.
leading Enterprise Risk Management (ERM) software package. ARM is recognized by independent analysts as having “the most extensive range of ERM capabilities currently available”. Unlike traditional, compliance- focused “GRC” solutions, ARM delivers far more value and capability to its users. With its robust and unique integrated approach, ARM is the only ERM solution that addresses the risk management needs of all parts of the business – from an individual department to the organization as a whole. From managing project and program risk to strategic business planning, ARM helps organizations identify, analyze, control, monitor, mitigate and report on risk across the enterprise.
The project is to design and manufacture a collaborative robot, which is a robot intended to physically interact with humans in a shared work space. The industrial robot is intended to work a specific task, protected by a barrier. The project focuses on designing a collaborative arm capable of working alongside with humans in workplace or home. The robotic arm is having a four degrees of freedom with a capacity to lift a weight of 300g. Robot Operating System (ROS) was used for coding the program. The arm can perform repeated actions like pick and place, soldering. It can detect human presence with the help of sensors. It can be easily reprogrammed for performing other actions.
ABSTRACT: This paper mainly introduces the calculation and design of the hydraulic arm of the disaster relief robot, and discusses the structural design of the main components of the hydraulic arm of the disaster relief robot, and the strength of the main force parts of the hydraulic arm Check. Completed the design of the hydraulic arm of the disaster relief robot.
The Present Control and Acquisition System uses LPC2148 16/32-bit RISC Microcontroller. It is cost effective and has high performance for general applications. An outstanding feature of the LPC2148 is its CPU core, a 16/32- bit ARM7TDMI RISC Processor (66MHz) designed by Advanced RISC Machines, Ltd., Hence, the processor has low power consumption and small size with a high instruction throughput and an excellent real-time interrupt response. Besides, LPC2148 has abundant integrated on-chip functions such as Bus Interfaces, Watch Dog Timer (WDT), and Real Time Clock (RTC) and so on. All these features facilitate the controller’s hardware and software design. Because the processor uses a pipeline to increase the speed of the flow of instructions, it allows several operations to take place simultaneously and the processing and memory systems to operate continuously. On the basis, Windows Operation System can be ported to the embedded system. Thus, the controller based on the ARM Processor can deal with much more complicated control tasks that most conventional . The embedded system uses FLASH and SDRAM memories for storage and program running.
In this paper, the effectiveness of the proposed method is demonstrated through experimental results using a 3-link dual-arm UVMS in actual un- derwater environment. Using the proposed method, in spite of large po- sition and attitude errors of the robot vehicle, good control performances of the arm’s end-tips to follow a pre-planned trajectory can be achieved. The uniqueness of the proposed method is that the desired joint signals are obtained from kinematic and momentum equations utilizing feedback of task space signals consists of (a) the position and attitude of vehicle and end-tips, and also (b) linear and angular velocities of the vehicle and end-tips. Moreover, the method can reduce the inﬂuence of modeling errors of hydrodynamic forces using the position, attitude and velocity feedback of the UVMS.
Over the past few decades, there has been a very abundant literature on conditional mean and volatility (CM V ) models because of their ability to describe both level and variability of a broad array of observed time series such as …nancial stock returns (see e.g. Engle, 1982; Nicholls and Quinn, 1982; Weiss, 1984; Bollerslev, 1986; Taylor, 1986; Tsay, 1987, 2002; Holan et al, 2010; Francq and Zakoïan, 2010). An essential common speci…cation for such models is that their conditional mean and conditional variance are stochastic, generally function of the past of the observed phenomenon, from which they can be evaluated for level and volatility predictions. In particular, when the conditional variance (resp. condi- tional mean) is non-stochastic the CM V model is simply called purely conditional mean (resp. purely conditional volatility) model. Among the most popular speci…cations are: the ARM A model with a GARCH innovation (ARM A-GARCH), the ARM A model with a stochastic volatility (ARM A-SV ) innovation, the ARM A model with a bilinear innova- tion (ARM A-BL), the subdiagonal bilinear (BL) model, the conditionally heteroskedastic ARM A (CHARM A) model, the double autoregressions (DAR) (Ling and Li, 2008; Chen et al, 2014) and the random coe¢cient autoregression (RCA) with a special case in which the random coe¢cient is …nite-valued like the Markov mixture autoregression (M AR) and the threshold autoregression (T AR). In fact, all aforementioned models are subclasses of the general class of weak (or nonlinear) ARM A models (e.g. Amendola and Francq, 2009) which consist of ARM A equations with uncorrelated, but not necessarily independent innovations. When the innovation is independent, the ARM A model is simply called strong (or linear).
The robot workspace (sometimes known as reachable space) is the place where the end effector (gripper) can reach. The workspace is dependent on the DOF, angle/translation limitations, the arm link lengths, the angle at which something must be picked up at, etc. The workspace is highly dependent on the configuration of the robot.
3wo fish showed a significant decrease in the occupancy and entry frequency of the conditioned arm during the test session (see Results Chapter 3.3.1). The conditioned response persisted for a period of approximately 15 minutes on average across individual fish. The gradual loss of conditioned aversion in the test session can be explained either by passive loss of the response, or by active relearning of the safety of the previously conditioned arm. Active relearning would depend on the presence of the visual cues (given their relevance in the paradigm, see Results Chapter 3.5.1), and would occur when the fish visits the arm with the conditioned pattern and receives no electric shock, thus building a new association of safety with the previously conditioned arm. Passive memory loss should be a function of time, and would happen independently of the presence of the visual cues. Experiments with a delay session before the test, during which all patterns were switched to uniform gray for 5 or 10 minutes, showed that the fish gradually lost the aversion, independent of the presence or absence of the patterns, i.e. the loss was a function of time (Results Chapter 3.3.4). However, the occupancy and the entry frequency of the shocked arm were still significantly reduced in the beginning of the test session even after a 10- minute delay (although the effect was smaller). An additional experiment with a longer delay session (e.g. 15 minutes long) could clarify if the aversive response would be completely gone by the end of the longer delay, or if instead there are more complex underlying kinetics.
In the present thesis, analysis is performed on the loader arm to optimize the arm from minimum stress and deflection. The model of the loader arm is changed by changing the limb lengths. The limb lengths are decreased from 900mm to 700mm and 500mm. The present used material is steel; it is replaced with Aluminum alloy 7075.The 3D models of the loader arm are done in Pro/Engineer. Analysis is done in Ansys. By observing the static analysis results, the
List randomization has been used to study several attitudes such as race, environment, drug use etc. In public health domain, list randomization is used to estimate base rates for risky sexual behaviors and risky sexual behaviors after alcohol consumption. In a population of college students, the list randomization revealed higher estimates of having had sex, having had sex without a condom, and having had sex without a condom after drinking compared to an anonymous self‐report survey (LaBrie and Earleywine 2000). In another study list randomization is applied to test respondent’s discomfort about Barack Obama being the first black president, list estimates suggest that 30 percent of white Americans were troubled by the prospect of Obama as the first black president (Tolbert et al, 2010). List randomization is also used in a study to determine if the support for same-sex marriage among the US citizens is overestimated because of it being socially desirable issue in some states in US. The findings suggest that there is no significant difference in estimates generated using direct questions and list randomization, indicating that the support for same sex marriage under direct questioning is not overestimated (Jeffrey R. Lax et al 2014). The research similar to this paper, estimates that magnitude of antigay sentiment and size of LGBT population from the sample from Mechanical Turk, in US. They find that the magnitude of antigay sentiment and the size of the lesbian, gay, bisexual, and transgender (LGBT) population are misestimated under direct questioning (Coffman et al, 2016). The existing literature on list randomization suggests that it uncovers the under reporting of socially undesirable issues, however the above studies also discuss the limitation of list randomization. List randomization leads to increased sampling variability, which results in larger variances and standard errors. This has been the major concerns for experimentalists in recent years. This need of reducing sampling variability has led to advancements in standard experimental protocol of list randomization, recent advancements to standard list randomization are discussed below.
The most common late complication observed was vaginal fibrosis. Grade III and IV vaginal fibrosis were seen in 16% in both arms. Grade III and IV rectal complications were seen in 2 cases (4%) of the study population (1 in each arm) (p value=1). 1 patient complained of RVF in Arm A and 1 patient in Arm B complained of severe proctitis. Grade III and IV bladder complications in the form of VVF were observed in 2 cases (4%) in Arm B.
The weight of the prosthesis, minus the weight of the terminal device, has been set to a maximum value of 5 pounds. During our third meeting with Cassie, she informed us that her right arm weighs 7 lbs and her current carbon fiber prosthesis weighs about 5 lbs (with the terminal device). Cassie informed us that the lighter the prosthesis is the better, and since carbon fiber is not being used in this design, keeping the prosthesis under 5 pounds was a medium risk requirement. In order to test this requirement, we analyzed the weight of the prosthesis by designing in 3D CAD software, inputting material densities, and summing up total weight. Furthermore, once the final prosthesis was manufactured, we were able to weigh the prosthesis.