A new interaction force decomposition maximizing compensating forces under physical work constraints

Decomposition of interaction forces in manipulation tasks has a long research tradition. Interaction forces are often split into robustness-reflective and accelerating forces. While this decomposition is typically performed for the synthesis of interaction forces to be applied for example in the context of robotic grasping, less attention has been paid to the analysis of measured, human interaction forces. Here we present a new decomposition approach for interaction force analysis. It extends the intuitive solution known in literature for the two finger grasp and combines it with a physically motivated bounding constraint, which allows the maximization of robustness reflective forces. Advantages of our approach are illustrated with an example and are compared to existing decomposition approaches. In contrast to existing approaches the new approach is not limited in the number of interaction points and incorporates forces which are physically possible only

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

Development of Object-Based Teleoperator Control for Unstructured Applications

For multi-fingered end effectors in unstructured applications, the main issues are control in the presence of uncertainties and providing grasp stability and object manipulability. The suggested concept in this thesis is object based teleoperator control which provides an intuitive way to control the robot in terms of the grasped object and reduces the operator\u27s conceptual constraints. The general control law is developed using a hierarchical control structure, i.e., human interface I gross motion control level in teleoperation control and fine motion control/object grasp stability in autonomous control. The gross motion control is required to provide the position/orientation of the Super Object (SO), and the sufficient grasping force to the fine motion control. Impedance control is applied to the gross motion control to respond to the environmental forces. The fine motion control consists of serially connecting the finger in position control and the Fingertip Actuation System (FAS) in force control. The FAS has a higher bandwidth response than does the finger actuation system and operates near the center of its joint range. The finger motion controller attempts not only to track the displacement of the FAS but also to provide an FAS centering action. Simulation experiments in both gross and fine motion control are performed. The integrated gross / flue motion control is implemented using the planar configuration of PUMA 560. The results show that the desired contact force can be maintained in the direction of FAS motion. The mathematical proof of system stability and the extension to spatial systems are required to complete the research

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)

The implications of embodiment for behavior and cognition: animal and robotic case studies

In this paper, we will argue that if we want to understand the function of the brain (or the control in the case of robots), we must understand how the brain is embedded into the physical system, and how the organism interacts with the real world. While embodiment has often been used in its trivial meaning, i.e. 'intelligence requires a body', the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. A number of case studies are presented to illustrate the concept. These involve animals and robots and are concentrated around locomotion, grasping, and visual perception. A theoretical scheme that can be used to embed the diverse case studies will be presented. Finally, we will establish a link between the low-level sensory-motor processes and cognition. We will present an embodied view on categorization, and propose the concepts of 'body schema' and 'forward models' as a natural extension of the embodied approach toward first representations.Comment: Book chapter in W. Tschacher & C. Bergomi, ed., 'The Implications of Embodiment: Cognition and Communication', Exeter: Imprint Academic, pp. 31-5

Object Manipulation under Hybrid Active/Passive Closure

In this paper, we discuss the manipulation of an object under hybrid active/passive closure. We show the orthogonality between the directions of active and passive force closures for general grasping systems. Based on the orthogonality, we decompose the dynamics of grasping system into the "active part" and the "passive part". By using the decomposition, we show that the grasped object can be manipulated only by considering the dynamics of the active part. We also consider how to determine the desired internal forces in order to satisfy frictional constraints during the manipulation. In order to verify the validity of our approach, some simulation results are shown

Optical Proximity Sensing for Pose Estimation During In-Hand Manipulation

During in-hand manipulation, robots must be able to continuously estimate the pose of the object in order to generate appropriate control actions. The performance of algorithms for pose estimation hinges on the robot's sensors being able to detect discriminative geometric object features, but previous sensing modalities are unable to make such measurements robustly. The robot's fingers can occlude the view of environment- or robot-mounted image sensors, and tactile sensors can only measure at the local areas of contact. Motivated by fingertip-embedded proximity sensors' robustness to occlusion and ability to measure beyond the local areas of contact, we present the first evaluation of proximity sensor based pose estimation for in-hand manipulation. We develop a novel two-fingered hand with fingertip-embedded optical time-of-flight proximity sensors as a testbed for pose estimation during planar in-hand manipulation. Here, the in-hand manipulation task consists of the robot moving a cylindrical object from one end of its workspace to the other. We demonstrate, with statistical significance, that proximity-sensor based pose estimation via particle filtering during in-hand manipulation: a) exhibits 50% lower average pose error than a tactile-sensor based baseline; b) empowers a model predictive controller to achieve 30% lower final positioning error compared to when using tactile-sensor based pose estimates.Comment: 8 pages, 6 figure

Dynamics and controls for robot manipulators with open and closed kinematic chain mechanisms

This dissertation deals with dynamics and controls for robot manipulators with open and closed kinematic chain mechanisms;Part I of this dissertation considers the problem of designing a class of robust algorithms for the trajectory tracking control of unconstrained single robot manipulator. The general control structure consists of two parts: The nominal control laws are first introduced to stabilize the system in the absence of uncertainties, then a class of robust nonlinear control laws are adopted to compensate for both the structured uncertainties and the unstructured uncertainties by using deterministic approach. The possible upper bounds of uncertainties are assumed to be known for the nonadaptive version of robust nonlinear controls. If information on these bounds is not available, then the adaptive bound of the robust controller is presented to overcome possible time-varying uncertainties (i.e., decentralized adaptive control scheme);Part II of the dissertation presents the efficient methodology of formulating system dynamics and hybrid position/force control for a single robot manipulator under geometric end-effector constraints. In order to facilitate dynamic analysis and control synthesis, the original joint-space dynamics (or a set of DAEs) is transformed into the constraint-space model through nonlinear transformations. Using the transformed dynamic model, a class of hybrid control laws are presented to manipulate the position and contact force at the end-effector simultaneously and accurately: the modified computed torque method, the robust adaptive controller, and the adaptive hybrid impedance controller;Part III of the dissertation deals with a mathematical modeling and coordinated control of multiple robot manipulators holding and transporting a rigid common object on the constraint surfaces. First, the kinematics and dynamics of multiple robot systems containing the closed-chain mechanisms are formulated from a unified viewpoint. After a series of model transformations, a new combined dynamic model is derived for dynamic analysis and control synthesis. Next, a class of hybrid position/force controllers are developed. The control laws can be used to simultaneously control the position of the object along the constraint surfaces and the contact forces (the internal grasping forces and the external constraint forces)

A Dynamic Manipulation Strategy for an Intervention Autonomous Underwater Vehicle

This paper presents the modelling and the control architecture of an Autonomous Underwater Vehicle for Intervention (I-AUV). Autonomous underwater manipulation with free-floating base is still an open topic of research, far from reaching an industrial product. Dynamic manipulation tasks, where relevant vehicle velocities are required during manipulation, over an additional challenge. In this paper, the accurate modelling of an I-AUV is described, not neglecting the interaction with the fluid. A grasp planning strategy is proposed and integrated in the control of the whole system. The performances of the I-AUV have been analysed by means of simulations of a dynamic manipulation task

Grasp plannind under task-specific contact constraints

Several aspects have to be addressed before realizing the dream of a robotic hand-arm system with human-like capabilities, ranging from the consolidation of a proper mechatronic design, to the development of precise, lightweight sensors and actuators, to the efficient planning and control of the articular forces and motions required for interaction with the environment. This thesis provides solution algorithms for a main problem within the latter aspect, known as the {\em grasp planning} problem: Given a robotic system formed by a multifinger hand attached to an arm, and an object to be grasped, both with a known geometry and location in 3-space, determine how the hand-arm system should be moved without colliding with itself or with the environment, in order to firmly grasp the object in a suitable way. Central to our algorithms is the explicit consideration of a given set of hand-object contact constraints to be satisfied in the final grasp configuration, imposed by the particular manipulation task to be performed with the object. This is a distinguishing feature from other grasp planning algorithms given in the literature, where a means of ensuring precise hand-object contact locations in the resulting grasp is usually not provided. These conventional algorithms are fast, and nicely suited for planning grasps for pick-an-place operations with the object, but not for planning grasps required for a specific manipulation of the object, like those necessary for holding a pen, a pair of scissors, or a jeweler's screwdriver, for instance, when writing, cutting a paper, or turning a screw, respectively. To be able to generate such highly-selective grasps, we assume that a number of surface regions on the hand are to be placed in contact with a number of corresponding regions on the object, and enforce the fulfilment of such constraints on the obtained solutions from the very beginning, in addition to the usual constraints of grasp restrainability, manipulability and collision avoidance. The proposed algorithms can be applied to robotic hands of arbitrary structure, possibly considering compliance in the joints and the contacts if desired, and they can accommodate general patch-patch contact constraints, instead of more restrictive contact types occasionally considered in the literature. It is worth noting, also, that while common force-closure or manipulability indices are used to asses the quality of grasps, no particular assumption is made on the mathematical properties of the quality index to be used, so that any quality criterion can be accommodated in principle. The algorithms have been tested and validated on numerous situations involving real mechanical hands and typical objects, and find applications in classical or emerging contexts like service robotics, telemedicine, space exploration, prosthetics, manipulation in hazardous environments, or human-robot interaction in general