1,407 research outputs found
Using multiple sensors for printed circuit board insertion
As more and more activities are performed in space, there will be a greater demand placed on the information handling capacity of people who are to direct and accomplish these tasks. A promising alternative to full-time human involvement is the use of semi-autonomous, intelligent robot systems. To automate tasks such as assembly, disassembly, repair and maintenance, the issues presented by environmental uncertainties need to be addressed. These uncertainties are introduced by variations in the computed position of the robot at different locations in its work envelope, variations in part positioning, and tolerances of part dimensions. As a result, the robot system may not be able to accomplish the desired task without the help of sensor feedback. Measurements on the environment allow real time corrections to be made to the process. A design and implementation of an intelligent robot system which inserts printed circuit boards into a card cage are presented. Intelligent behavior is accomplished by coupling the task execution sequence with information derived from three different sensors: an overhead three-dimensional vision system, a fingertip infrared sensor, and a six degree of freedom wrist-mounted force/torque sensor
Design of intelligent multifinger gripper for a robotic arm using a DSP-based fuzzy controller
The design and modeling of a robotic arm
gripper that has elements of intelligent decision making
while grasping object has been recently discussed. This new
system is different in using an appropriate controlling
scheme so that the correct force is applied to pick an object
without dropping or crushing it. This is achieved by
controlling the shear stresses at the interface material
between finger-ends and the object using smart sensors and
intelligent controller. A new slip sensor that is based on the
operation of optical encoder is used to monitor the slip rate
as a result of insufficient force being applied to pick an
object. A two-stage control scheme is suggested for the
implementation of this system. First a limit switch is used
to control the positioning of the fingers thereby solving the
problem of uncertainty in the location and orientation of the
object. Then, to ensure that an appropriate force is used in
picking up an object a fuzzy logic controller is used. The
use of TMS320C24XX series DSP controller to implement
the control strategy provides the flexibility needed in
altering the control code and the prototype can be tested at
low cost
Inverse kinematic analysis of 4 DOF pick and place arm robot manipulator using fuzzy logic controller
The arm robot manipulator is suitable for substituting humans working in tomato plantation to ensure tomatoes are handled efficiently. The best design for this robot is four links with robust flexibility in x, y, and z-coordinates axis. Inverse kinematics and fuzzy logic controller (FLC) application are for precise and smooth motion. Inverse kinematics designs the most efficient position and motion of the arm robot by adjusting mechanical parameters. The FLC utilizes data input from the sensors to set the right position and motion of the end-effector. The predicted parameters are compared with experimental results to show the effectiveness of the proposed design and method. The position errors (in x, y, and z-axis) are 0.1%, 0.1%, and 0.04%. The rotation errors of each robot links (θ1, θ2, and θ3) are 0%, 0.7% and 0.3%. The FLC provides the suitable angle of the servo motor (θ4) responsible in gripper motion, and the experimental results correspond to FLC’s rules-based as the input to the gripper motion system. This setup is essential to avoid excessive force or miss-placed position that can damage tomatoes. The arm robot manipulator discussed in this study is a pick and place robot to move the harvested tomatoes to a packing system
Control techniques for mechatronic assisted surgery
The treatment response for traumatic head injured patients can be improved by
using an autonomous robotic system to perform basic, time-critical emergency neurosurgery,
reducing costs and saving lives. In this thesis, a concept for a neurosurgical robotic system is proposed to perform three specific emergency neurosurgical procedures; they are the placement of an intracranial pressure monitor, external
ventricular drainage, and the evacuation of chronic subdural haematoma. The control
methods for this system are investigated following a curiosity led approach. Individual problems are interpreted in the widest sense and solutions posed that are general in nature. Three main contributions result from this approach: 1)
a clinical evidence based review of surgical robotics and a methodology to assist in their evaluation, 2) a new controller for soft-grasping of objects, and 3) new propositions and theorems for chatter suppression sliding mode controllers. These contributions directly assist in the design of the control system of the neurosurgical robot and, more broadly, impact other areas outside the narrow con nes of the target application. A methodology for applied research in surgical robotics is proposed. The methodology sets out a hierarchy of criteria consisting of three tiers, with the most important being the bottom tier and the least being the top tier. It is argued that
a robotic system must adhere to these criteria in order to achieve acceptability. Recent commercial systems are reviewed against these criteria, and are found to conform up to at least the bottom and intermediate tiers. However, the lack of
conformity to the criteria in the top tier, combined with the inability to conclusively
prove increased clinical benefit, particularly symptomatic benefit, is shown to be hampering the potential of surgical robotics in gaining wide establishment. A control scheme for soft-grasping objects is presented. Grasping a soft or fragile object requires the use of minimum contact force to prevent damage or deformation. Without precise knowledge of object parameters, real-time feedback
control must be used to regulate the contact force and prevent slip. Moreover, the controller must be designed to have good performance characteristics to rapidly modulate the fingertip contact force in response to a slip event. A fuzzy sliding mode controller combined with a disturbance observer is proposed for contact force control and slip prevention. The robustness of the controller is evaluated through
both simulation and experiment. The control scheme was found to be effective and robust to parameter uncertainty. When tested on a real system, however, chattering phenomena, well known to sliding mode research, was induced by the
unmodelled suboptimal components of the system (filtering, backlash, and time delays). This reduced the controller performance. The problem of chattering and potential solutions are explored. Real systems using sliding mode controllers, such as the control scheme for soft-grasping, have a tendency to chatter at high frequencies. This is caused by the sliding mode
controller interacting with un-modelled parasitic dynamics at the actuator-input
and sensor-output of the plant. As a result, new chatter-suppression sliding mode controllers have been developed, which introduce new parameters into the system. However, the effect any particular choice of parameters has on system performance
is unclear, and this can make tuning the parameters to meet a set of performance
criteria di cult. In this thesis, common chatter-suppression sliding mode control
strategies are surveyed and simple design and estimation methods are proposed.
The estimation methods predict convergence, chattering amplitude, settling time,
and maximum output bounds (overshoot) using harmonic linearizations and invariant
ellipsoid sets
Robust contact force controller for slip prevention in a robotic gripper
Grasping a soft or fragile object requires the use of minimum contact force to prevent damage or deformation. Without precise knowledge of object parameters, real-time feedback control must be used with a suitable slip sensor to regulate the contact force and prevent slip. Furthermore, the controller must be designed to have good performance characteristics to rapidly modulate the fingertip contact force in response to a slip event. In this paper, a fuzzy sliding mode controller combined with a disturbance observer is proposed for contact force control and slip prevention. The controller is based on a system model that is suitable for a wide class of robotic gripper configurations. The robustness of the controller is evaluated through both simulation and experiment. The control scheme was found to be effective and robust to parameter uncertainty. When tested on a real system, however, chattering phenomena, well known to sliding mode research, was induced by the unmodelled suboptimal components of the system (filtering, backlash, and time delays), and the controller performance was reduced
Hands tracking and fuzzy speed control to improve human-robot collaboration
Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáThe demand of collaborative robots has been growing in the industry in general, and with it the need for new ways to improve and make this work environment between human and robot safer and efficient. The objective of this work is to improve and make this environment safer and efficient by controlling the robot’s speed using a fuzzy approach and by getting track of the hand of the operator. For this purpose, the UR3 robot from Universal Robots and Leap Motion was used, which is a sensor capable of detecting the hand, as well as its movements, with the data obtained it was possible to create a system that has the robot’s speed as an output through fuzzy logic, and using the distance between the hand and the gripper obtained from the Leap Motion and UR3 data
respectively as input to the fuzzy logic. With this it was possible to achieve satisfactory speed control, moreover, in all the tests performed the approach proved to be able to avoid collisions, and with the testing of different defuzzification methods in the fuzzy control, it was also possible to achieve smooth speed control for some of the methods used, with this in mind the system showed promise for improving Human-Robot Collaboration.A procura de robĂ´s colaborativos tem crescido na indĂşstria em geral, e com ela a necessidade de novas formas de melhorar e tornar este ambiente de trabalho entre o ser humano e o robĂ´ mais seguro e eficiente. O objetivo deste trabalho Ă© melhorar e tornar este ambiente mais seguro e eficiente, controlando a velocidade do robĂ´ atravĂ©s de uma abordagem fuzzy e da localização da mĂŁo do operador. Para o efeito, foi utilizado o robĂ´ UR3 dos Universal Robots e do Leap Motion, o qual Ă© um sensor capaz de detectar a mĂŁo, bem como os seus movimentos. Com os dados obtidos foi possĂvel criar um sistema com a lĂłgica fuzzy, tendo como saĂda a velocidade do robĂ´ e a entrada a distância entre a mĂŁo e a garra, obtida pelos dados do Leap Motion e do UR3, respectivamente. Com isto foi possĂvel obter um controlo de velocidade satisfatĂłrio, alĂ©m disso, em todos os testes realizados a abordagem provou conseguir evitar colisões, e com o teste de diferentes mĂ©todos de defuzzificação no controle fuzzy, tambĂ©m foi possĂvel alcançar um controle suave da velocidade para alguns dos mĂ©todos utilizados, com isto em mente o sistema mostrou-se promissor para melhorar a Colaboração Humano-Robot
Human-robot interaction using a behavioural control strategy
PhD ThesisA topical and important aspect of robotics research is in the area of human-robot interaction (HRI), which addresses the issue of cooperation between a human and a robot to allow tasks to be shared in a safe and reliable manner. This thesis focuses on the design and development of an appropriate set of behaviour strategies for human-robot interactive control by first understanding how an equivalent human-human interaction (HHI) can be used to establish a framework for a robotic behaviour-based approach. To achieve the above goal, two preliminary HHI experimental investigations were initiated in this study. The first of which was designed to evaluate the human dynamic response using a one degree-of-freedom (DOF) HHI rectilinear test where the handler passes a compliant object to the receiver along a constrained horizontal path. The human dynamic response while executing the HHI rectilinear task has been investigated using a Box-Behnken design of experiments [Box and Hunter, 1957] and was based on the McRuer crossover model [McRuer et al. 1995].
To mimic a real-world human-human object handover task where the handler is able to pass an object to the receiver in a 3D workspace, a second more substantive one DOF HHI baton handover task has been developed. The HHI object handover tests were designed to understand the dynamic behavioural characteristics of the human participants, in which the handler was required to dexterously pass an object to the receiver in a timely and natural manner. The profiles of interactive forces between the handler and receiver were measured as a function of time, and how they are modulated whilst performing the tasks, was evaluated. Three key parameters were used to identify the physical characteristics of the human participants, including: peak interactive force (fmax), transfer time (Ttrf), and work done (W). These variables were subsequently used to design and develop an appropriate set of force and velocity control strategies for a six DOF Stäubli robot manipulator arm (TX60) working in a human-robot interactive environment. The optimal design of the software and hardware controller implementation for the robot system has been successfully established in keeping with a behaviour-based approach. External force control based on proportional plus integral (PI) and fuzzy logic control (FLC) algorithms were adopted to control the robot end effector velocity and interactive force in real-time.
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The results of interactive experiments with human-to-robot and robot-to-human handover tasks allowed a comparison of the PI and FLC control strategies. It can be concluded that the quantitative measurement of the performance of robot velocity and force control can be considered acceptable for human-robot interaction. These can provide effective performance during the robot-human object handover tasks, where the robot was able to successfully pass the object from/to the human in a safe, reliable and timely manner. However, after careful analysis with regard to human-robot handover test results, the FLC scheme was shown to be superior to PI control by actively compensating for the dynamics in the non-linear system and demonstrated better overall performance and stability. The FLC also shows superior performance in terms of improved sensitivity to small error changes compared to PI control, which is an advantage in establishing effective robot force control. The results of survey responses from the participants were in agreement with the parallel test outcomes, demonstrating significant satisfaction with the overall performance of the human-robot interactive system, as measured by an average rating of 4.06 on a five point scale.
In brief, this research has contributed the foundations for long-term research, particularly in the development of an interactive real-time robot-force control system, which enables the robot manipulator arm to cooperate with a human to facilitate the dextrous transfer of objects in a safe and speedy manner.Thai government and Prince of Songkla University (PSU
Neuromorphic event-based slip detection and suppression in robotic grasping and manipulation
Slip detection is essential for robots to make robust grasping and fine
manipulation. In this paper, a novel dynamic vision-based finger system for
slip detection and suppression is proposed. We also present a baseline and
feature based approach to detect object slips under illumination and vibration
uncertainty. A threshold method is devised to autonomously sample noise in
real-time to improve slip detection. Moreover, a fuzzy based suppression
strategy using incipient slip feedback is proposed for regulating the grip
force. A comprehensive experimental study of our proposed approaches under
uncertainty and system for high-performance precision manipulation are
presented. We also propose a slip metric to evaluate such performance
quantitatively. Results indicate that the system can effectively detect
incipient slip events at a sampling rate of 2kHz () and
suppress them before a gross slip occurs. The event-based approach holds
promises to high precision manipulation task requirement in industrial
manufacturing and household services.Comment: 18 pages, 14 figure
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
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