Position Control of Linkage Underactuated Robotic Hand

In this study a proposed PID control system for (Ca.U.M.Ha) robotic hand with a finger and a thumb introduced, to control grasping cylindrical objects made from different materials soft and hard within a range of (48-150) mm in diameter . A samples of PID response figures for object that need just a finger, and object that needs a finger with a thumb introduced in additional to the figures of actuators voltage needed for both cases through grasping. Keywords: Linkage , underactuated, position  PID contro

Performance of modified jatropha oil in combination with hexagonal boron nitride particles as a bio-based lubricant for green machining

This study evaluates the machining performance of newly developed modified jatropha oils (MJO1, MJO3 and MJO5), both with and without hexagonal boron nitride (hBN) particles (ranging between 0.05 and 0.5 wt%) during turning of AISI 1045 using minimum quantity lubrication (MQL). The experimental results indicated that, viscosity improved with the increase in MJOs molar ratio and hBN concentration. Excellent tribological behaviours is found to correlated with a better machining performance were achieved by MJO5a with 0.05 wt%. The MJO5a sample showed the lowest values of cutting force, cutting temperature and surface roughness, with a prolonged tool life and less tool wear, qualifying itself to be a potential alternative to the synthetic ester, with regard to the environmental concern

Active compliance control strategies for multifingered robot hand

Safety issues have to be enhanced when the robot hand is grasping objects of different shapes, sizes and stiffness. The inability to control the grasping force and finger stiffness can lead to unsafe grasping environment. Although many researches have been conducted to resolve the grasping issues, particularly for the object with different shape, size and stiffness, the grasping control still requires further improvement. Hence, the primary aim of this work is to assess and improve the safety of the robot hand. One of the methods that allows a safe grasping is by employing an active compliance control via the force and impedance control. The implementation of force control considers the proportional–integral–derivative (PID) controller. Meanwhile, the implementation of impedance control employs the integral slidingmode controller (ISMC) and adaptive controller. A series of experiments and simulations is used to demonstrate the fundamental principles of robot grasping. Objects with different shape, size and stiffness are tested using a 3-Finger Adaptive Robot Gripper. The work introduces the Modbus remote terminal unit [RTU] protocol, a low-cost force sensor and the Arduino IO Package for a real-time hardware setup. It is found that, the results of the force control via PID controller are feasible to maintain the grasped object at certain positions, depending on the desired grasping force (i.e., 1N and 8N). Meanwhile, the implementation of impedance control via ISMC and adaptive controller yields multiple stiffness levels for the robot fingers and able to reduce collision between the fingers and the object. However, it was found that the adaptive controller produces better impedance control results as compared to the ISMC, with a 33% efficiency improvement. This work lays important foundations for long-term related research, particularly in the field of active compliance control that can be beneficial to human–robot interaction (HRI)

Myoelectric forearm prostheses: State of the art from a user-centered perspective

User acceptance of myoelectric forearm prostheses is currently low. Awkward control, lack of feedback, and difficult training are cited as primary reasons. Recently, researchers have focused on exploiting the new possibilities offered by advancements in prosthetic technology. Alternatively, researchers could focus on prosthesis acceptance by developing functional requirements based on activities users are likely to perform. In this article, we describe the process of determining such requirements and then the application of these requirements to evaluating the state of the art in myoelectric forearm prosthesis research. As part of a needs assessment, a workshop was organized involving clinicians (representing end users), academics, and engineers. The resulting needs included an increased number of functions, lower reaction and execution times, and intuitiveness of both control and feedback systems. Reviewing the state of the art of research in the main prosthetic subsystems (electromyographic [EMG] sensing, control, and feedback) showed that modern research prototypes only partly fulfill the requirements. We found that focus should be on validating EMG-sensing results with patients, improving simultaneous control of wrist movements and grasps, deriving optimal parameters for force and position feedback, and taking into account the psychophysical aspects of feedback, such as intensity perception and spatial acuity

Slippage detection for grasping force control of robotic hand using force sensing resistors

This paper presents the formulation of a nonlinear adaptive backstepping force control in grasping weight-varying objects using robotic hand driven by Pneumatic Artificial Muscle (PAM). The modelling and control problems arise from the high nonlinear PAM dynamics and the inherent hysteresis leading to a lack of robustness in the hand’s performance. The robotic finger and the PAM actuator been mathematically modelled as a nonlinear second order system based on an empirical approach. An adaptive backstepping controller has been designed for force control of the pneumatic hand. The estimator of the system uncertainty is incorporated into the proposed control law and a slip detection strategy is introduced to grasp objects with changing weights. The simulation and experimental results show that the robotic hand can maintain grasping an object and stop further slippage when its weight is increased up to 500 g by detecting the slip signal from the force sensor. The results also have proven that the adaptive backstepping controller is capable to compensate the uncertain coulomb friction force of PAM actuator with maximum hysteresis error 0.18◦

Innovative robot hand designs of reduced complexity for dexterous manipulation

This thesis investigates the mechanical design of robot hands to sensibly reduce the system complexity in terms of the number of actuators and sensors, and control needs for performing grasping and in-hand manipulations of unknown objects. Human hands are known to be the most complex, versatile, dexterous manipulators in nature, from being able to operate sophisticated surgery to carry out a wide variety of daily activity tasks (e.g. preparing food, changing cloths, playing instruments, to name some). However, the understanding of why human hands can perform such fascinating tasks still eludes complete comprehension. Since at least the end of the sixteenth century, scientists and engineers have tried to match the sensory and motor functions of the human hand. As a result, many contemporary humanoid and anthropomorphic robot hands have been developed to closely replicate the appearance and dexterity of human hands, in many cases using sophisticated designs that integrate multiple sensors and actuators---which make them prone to error and difficult to operate and control, particularly under uncertainty. In recent years, several simplification approaches and solutions have been proposed to develop more effective and reliable dexterous robot hands. These techniques, which have been based on using underactuated mechanical designs, kinematic synergies, or compliant materials, to name some, have opened up new ways to integrate hardware enhancements to facilitate grasping and dexterous manipulation control and improve reliability and robustness. Following this line of thought, this thesis studies four robot hand hardware aspects for enhancing grasping and manipulation, with a particular focus on dexterous in-hand manipulation. Namely: i) the use of passive soft fingertips; ii) the use of rigid and soft active surfaces in robot fingers; iii) the use of robot hand topologies to create particular in-hand manipulation trajectories; and iv) the decoupling of grasping and in-hand manipulation by introducing a reconfigurable palm. In summary, the findings from this thesis provide important notions for understanding the significance of mechanical and hardware elements in the performance and control of human manipulation. These findings show great potential in developing robust, easily programmable, and economically viable robot hands capable of performing dexterous manipulations under uncertainty, while exhibiting a valuable subset of functions of the human hand.Open Acces

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

Nonlinear control strategy for a cost effective myoelectric prosthetic hand

The loss of a limb tremendously impacts the life of the affected individual. In the past decades, researchers have been developing artificial limbs that may return some of the missing functions and cosmetics. However, the development of dexterous mechanisms capable of mimicking the function of the human hand is a complex venture. Even though myoelectric prostheses have advanced, several issues remain to be solved before an artificial limb may be comparable to its human counterpart. Moreover, the high cost of advanced limbs prevents their widespread use among the low-income population. This dissertation presents a strategy for the low-level of control of a cost effective robotic hand for prosthetic applications. The main purpose of this work is to reduce the high cost associated with limb replacement. The presented strategy uses an electromyographic signal classifier, which detects user intent by classifying 4 different wrist movements. This information is supplied as 4 different pre-shapes of the robotic hand to the low-level of control for safely and effectively performing the grasping tasks. Two proof-of-concept prototypes were implemented, consisting on five-finger underactuated hands driven by inexpensive DC motors and equipped with low-cost sensors. To overcome the limitations and nonlinearities of inexpensive components, a multi-stage control methodology was designed for modulating the grasping force based on slippage detection and nonlinear force control. A multi-stage control methodology for modulating the grasping force based on slippage detection and nonlinear force control was designed. The two main stages of the control strategy are the force control stage and the detection stage. The control strategy uses the force control stage to maintain a constant level of force over the object. The results of the experiments performed over this stage showed a rising time of less than 1 second, force overshoot of less than 1 N and steady state error of less than 0.15 N. The detection stage is used to monitor any sliding of the object from the hand. The experiments performed over this stage demonstrated a delay in the slip detection process of less than 200 milliseconds. The initial force, and the amount of force incremented after sliding is detected, were adjusted to reduce object displacement. Experiments were then performed to test the control strategy on situations often encountered in the ADL. The results showed that the control strategy was able to detect the dynamic changes in mass of the object and to successfully adjust the grasping force to prevent the object from dropping. The evaluation of the proposed control strategy suggests that this methodology can overcome the limitation of inexpensive sensors and actuators. Therefore, this control strategy may reduce the cost of current myoelectric prosthesis. We believe that the work presented here is a major step towards the development of a cost effective myoelectric prosthetic hand

Model-based and Model-Free Robot Control : A Review

Robot control is one of the key aspects of robotics research. Models are essential tools in robotics, such as the robot’s own body dynamics and kinematics models, actuator/motor models, and the models of external controllable objects. In this paper, we review the latest advances in model-based and model-free ap-proaches with a strong focus on robot control. Based on the designed search strategy, several prevailing control approaches are classified and discussed ac-cording to their control strategies. An insight into the gripper control is also explored. Then the research problems and applicability of the control methods are discussed by investigating their merits and demerits. Based on the discussion, we summarize the challenges and future research trends of robot control