Measuring inefficiency in the rubber manufacturing industry

Malaysia is the fifth largest producer of natural rubber in the world after Thailand, Indonesia, Vietnam and China as well as producing rubber products exported to more than 190 countries worldwide. However, the slowdown in growth of major importers such as China, the European Union and the United States and the perception of stock surplus as output exceeds demand led to fluctuating rubber production performance over the period 2010 to 2016. Hence, this article aims at examining the level of technical efficiency (TE) and to analyze the determinants of the inefficiencies of the rubber manufacturing industry. The analysis was conducted using the latest 145 firms’ data obtained from the Department of Statistics Malaysia (DOS) and using the Stochastic Frontier Analysis (SFA) method. The results showed that the overall TE level was high while the determinants such as the capital-labor ratio, wage rate and firm size had a negative and significant impact that could reduce industrial technical efficiencies. The policy implication is that the rubber manufacturing industry needs to focus on high technological production investment, increase employee motivation through wage increment and create more strategic cooperation with international industry

An instrumented manipulandum for human grasping studies

This work presents a novel haptic device to study human grasp, which integrates different technological solutions thus enabling, for the first time, to achieve: (i) a complete grasp characterization in terms of contact forces and moments; (ii) an estimation of contact point location for varying-orientation contact surfaces; (iii) a compensation of force/torque offsets and estimation of the mass and center of mass of the device, for different orientations and configurations in the workspace; (iv) different stiffness properties for the contact points, i.e. rigid, compliant non-deformable and compliant deformable, thus allowing to study the effects of cutaneous cues in multi-finger grasps. In addition, given the modularity of the architecture and the simple mechanism to attach/detach the contact modules, this structure can be easily modified in order to analyze different multi-finger grasp configurations. The effectiveness of this device was experimentally demonstrated and applications to neuroscientific studies and state of the art of devices for similar investigations are discussed in depth within the text

Modeling Compliant Grasps Exploiting Environmental Constraints

In this paper we present a mathematical framework to describe the interaction between compliant hands and environmental constraints during grasping tasks. In the proposed model, we considered compliance at wrist, joint and contact level. We modeled the general case in which the hand is in contact with the object and the surrounding environment. All the other contact cases can be derived from the proposed system of equations. We performed several numerical simulation using the SynGrasp Matlab Toolbox to prove the consistency of the proposed model. We tested different combinations of compliance as well as different reference inputs for the hand/arm system considered. This work has to be intended as a tool for compliant hand designer since it allows to tune compliance at different levels before the real hand realization. Furthermore, the same framework can be used for compliant hand simulation in order to study the interaction with the environmental constrains and to plan complex manipulation tasks

Exploitation of environmental constraints in human and robotic grasping

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.We investigate the premise that robust grasping performance is enabled by exploiting constraints present in the environment. These constraints, leveraged through motion in contact, counteract uncertainty in state variables relevant to grasp success. Given this premise, grasping becomes a process of successive exploitation of environmental constraints, until a successful grasp has been established. We present support for this view found through the analysis of human grasp behavior and by showing robust robotic grasping based on constraint-exploiting grasp strategies. Furthermore, we show that it is possible to design robotic hands with inherent capabilities for the exploitation of environmental constraints

A novel type of compliant and underactuated robotic hand for dexterous grasping

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The usefulness and versatility of a robotic end-effector depends on the diversity of grasps it can accomplish and also on the complexity of the control methods required to achieve them. We believe that soft hands are able to provide diverse and robust grasping with low control complexity. They possess many mechanical degrees of freedom and are able to implement complex deformations. At the same time, due to the inherent compliance of soft materials, only very few of these mechanical degrees have to be controlled explicitly. Soft hands therefore may combine the best of both worlds. In this paper, we present RBO Hand 2, a highly compliant, underactuated, robust, and dexterous anthropomorphic hand. The hand is inexpensive to manufacture and the morphology can easily be adapted to specific applications. To enable efficient hand design, we derive and evaluate computational models for the mechanical properties of the hand's basic building blocks, called PneuFlex actuators. The versatility of RBO Hand 2 is evaluated by implementing the comprehensive Feix taxonomy of human grasps. The manipulator's capabilities and limits are demonstrated using the Kapandji test and grasping experiments with a variety of objects of varying weight. Furthermore, we demonstrate that the effective dimensionality of grasp postures exceeds the dimensionality of the actuation signals, illustrating that complex grasping behavior can be achieved with relatively simple control

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)

Robust Grasp with Compliant Multi-Fingered Hand

As robots find more and more applications in unstructured environments, the need for grippers able to grasp and manipulate a large variety of objects has brought consistent attention to the use of multi-fingered hands. The hardware development and the control of these devices have become one of the most active research subjects in the field of grasping and dexterous manipulation. Despite a large number of publications on grasp planning, grasping frameworks that strongly depend on information collected by touching the object are getting attention only in recent years. The objective of this thesis focuses on the development of a controller for a robotic system composed of a 7-dof collaborative arm + a 16-dof torque-controlled multi-fingered hand to successfully and robustly grasp various objects. The robustness of the grasp is increased through active interaction between the object and the arm/hand robotic system. Algorithms that rely on the kinematic model of the arm/hand system and its compliance characteristics are proposed and tested on real grasping applications. The obtained results underline the importance of taking advantage of information from hand-object contacts, which is necessary to achieve human-like abilities in grasping tasks

Development and validation of haptic devices for studies on human grasp and rehabilitation

This thesis aims to develop and to validate a new set of devices for accurate investigation of human finger stiffness and force distribution in grasping tasks. The ambitious goal of this research is twofold: 1) to advance the state of art on human strategies in manipulation tasks and provide tools to assess rehabilitation procedure, 2) to investigate human strategies for impedance control that can be used for human robot interaction and control of myoelectric prosthesis. The first part of this thesis describes two types of systems that enable to achieve a complete set of measurements on force distribution and contact point locations. More specifically, this part includes: (i) the design process and validation of tripod grasp devices with controllable stiffness at the contact to be used also for rehabilitation purposes, and (ii) the validation of multi-digit wearable sensor system. Results on devices validation as well as illustrative measurement examples are reported and discussed. The effectiveness of these devices in grasp analysis was also experimentally demonstrated and applications to neuroscientific studies are discussed. In the second part of this thesis, the tripod devices are exploited in two different studies to investigate stiffness regulation principles in humans. The first study provides evidence on the existence of coordinated stiffening patterns in human hand fingers and establishes initial steps towards a real-time and effective modelling of finger stiffness in tripod grasp. This pattern further supports the evidence of synergistic control in human grasping. To achieve this goal, the endpoint stiffness of the thumb, index and middle fingers of healthy subjects are experimentally identified and correlated with the electromyography (EMG) signals recorded from a dominant antagonistic pair of the forearm muscles. Our findings suggest that the magnitude of the stiffness ellipses at the fingertips grows in a coordinated way, subsequent to the co-contraction of the forearm muscles. The second study presents experimental findings on how humans modulate their hand stiffness while grasping object of varying levels of compliance. Subjects perform a grasp and lift task with a tripod-grasp object with contact surfaces of variable compliance; EMG from the main finger flexor and extensor muscles was recorded along with force and torque data at the contact points. A significant increase in the extensor muscle and cocontraction levels is evidenced with an increasing compliance at the contact points. Overall results give solid evidence on the validity and utility of the proposed devices to investigate human grasp proprieties. The underlying motor control principles that are exploited by humans in the achievement of a reliable and robust grasp can be potentially integrated into the control framework of robotic or prosthetic hands to achieve a similar interaction performance

Human-Inspired Force Compliant Grasping Primitives

<p>We address the problem of grasping everyday ob- jects that are small relative to an anthropomorphic hand, such as pens, screwdrivers, cellphones, and hammers from their nat- ural poses on a support surface, e.g., a table top. In such con- ditions, state of the art grasp generation techniques fail to pro- vide robust, achievable solutions due to either ignoring or try- ing to avoid contact with the support surface. In contrast, when people grasp small objects, they often make use of substan- tial contact with the support surface. In this paper we give re- sults of human subjects grasping studies which show the ex- tent and characteristics of environment contact under differ- ent task conditions. We develop a simple closed-loop hybrid grasping controller that mimics this interactive, contact-rich strategy by a position-force, pre-grasp and landing strategy for finger placement. The approach uses a compliant control of the hand during the grasp and release of objects in order to preserve safety. We conducted extensive robotic grasping ex- periments on a variety of small objects with similar shape and size. The results demonstrate that our approach is robust to lo- calization uncertainties and applies to many everyday objects.</p