灵巧手抓持规划的虚拟仿真方法

本文介绍在虚拟环境中,通过仿真分析的手段来研究机器人灵巧手抓持规划方案的方法。研究中以人的经验为指导,根据手、物的形状及尺寸等相对关系初步给出定性的抓持方案,以此为基础在虚拟环境中对机器人灵巧手的抓持过程进行仿真分析,判定所给出的抓持规划是否能实现在虚拟环境中的稳定抓持。然后在可行方案的基础上进一步对灵巧手的抓持点位置及抓持姿态进行优化,最终可得到机器人灵巧手对于特定被抓持物的较令人满意的抓持规划方案。     

面向任务的三指手机器人抓取规划研究

本文给出了一种面向任务的三指手爪抓取规划的思路及研究方法，首先根据人手抓取姿态的分类，总结出典型的机器人抓取姿态，并以三指手爪来完成抓取，然后综合考虑任务要求、对象物体的几何物理特性及环境信息，经任务分析，推理出抓取姿态，并通过寻找特征平衡，确定出抓取平面，再在抓取现上进一步规划出３个抓取点，最终完成抓取规划过程。     

Direct Virtual-hand Interface in Robot Assembly Programming

For a long time, robot assembly programming has been produced in two environments: on-line and off-line. On-line robot programming uses the actual robot for the experiments performing a given task; off-line robot programming develops a robot program in either an autonomous system with a high-level task planner and simulation or a 2D graphical user interface linked to other system components. This paper presents a whole hand interface for more easily performing robotic assembly tasks in the virtual tenvironment. The interface is composed of both static hand shapes (states) and continuous hand motions (modes). Hand shapes are recognized as discrete states that trigger the control signals and commands, and hand motions are mapped to the movements of a selected instance in real-time assembly. Hand postures are also used for specifying the alignment constraints and axis mapping of the hand-part coordinates. The basic virtual-hand functions are constructed through the states and modes developing the robotic assembly program. The assembling motion of the object is guided by the user immersed in the environment to a path such that no collisions will occur. The fine motion in controlling the contact and ending position/orientation is handled automatically by the system using prior knowledge of the parts and assembly reasoning. One assembly programming case using this interface is described in detail in the paper.     

Experience-based optimization of universal manipulation strategies for industrial assembly tasks

The trend towards smaller lot sizes and shorter product life cycles requires automation solutions with higher flexibility. Today’s robotic systems often are uneconomical for frequently changing boundary conditions and varying tasks due to high engineering costs needed for a well-defined supply of parts and pallets. At the same time, even small inaccuracies due to shape deviations in parts or pallets often cause high downtime. This work contributes to the robustness of industrial assembly processes with high inaccuracy concurrent to narrow tolerances. Therefore, contact-based manipulation strategies are defined, which are model-free and object-independent and solve common industrial tasks as palletizing, packaging and machine feeding. While the strategies are robust to inaccuracy up to 5 mm/5° due to localization uncertainty or object displacement, they handle usual industrial assembly tolerance of far below 1mm. The necessary flexibility and reusability for new tasks is guaranteed by hierarchical decomposition into atomic sub-strategies. In order to accelerate the execution, the manipulation strategies are customized to each specific task by unsupervised experience-based learning. The flexibility of the manipulation strategies and the progress in cycle time during the execution are shown on common industrial tasks with varying objects, tolerances and inaccuracies.     

Development of a multifingered robotic hand with the thenar grasp function

ABSTRACT

Manipulation of objects after grasping is an important research topic for robotic hands. In this research, we propose a grip method based on the thenar opposition, which is rarely handled in the framework of conventional precision and power grasps and useful in withdrawing a large torque after the grip, and develop a robotic hand that can realize the grasp as well as normal grasps. To this end, we propose methods to evaluate the thenar opposition and the variety of grasps based on the joint alignment of the thumb. Based on these methods, we determine the kinematic structure of the robotic hand and develop it with gear train transmissions and a soft skin. Experiments are implemented to demonstrate that the robotic hand realizes various grasps and a gripping force sufficient to withstand the torque that opens tightly clamped hand valves.     

An autonomous mobile manipulator for assembly tasks

The fundamental difference between autonomous robotic assembly and traditional hard automation, currently utilized in large-scale manufacturing production, lies in the specific approaches used in locating, acquiring, manipulating, aligning, and assembling parts. An autonomous robotic assembly manipulator offers high flexibility and high capability to deal with the inherent system uncertainties, unknowns, and exceptions. This paper presents an autonomous mobile manipulator that effectively overcomes inherent system uncertainties and exceptions by utilizing control strategies that employ coordinated control, combine visual and force servoing, and incorporate sophisticated reactive task control. The mobile manipulation system has been demonstrated experimentally to achieve high reliability for a “peg-in-hole” type of insertion assembly task that is commonly encountered in automotive wiring harness assembly.     

Mutual information-enhanced digital twin promotes vision-guided robotic grasping

Vision-guided learning for autonomous robotic manipulations is a wide-ranging and high-impact topic in the context of smart manufacturing. Most learning strategies are object-centered or prior information-dependent, which likely lead to the problems of generalization across objects or scenes. To alleviate this, this work presented an embodiment decision-making method by the marriage between the digital twin epistemology and information-theoretic approach. The initial insight was that the mutual information generated in the interactions between the available vision models and real-world perceptions could decrease the uncertainty of sensing-action processes. Further, the real-time interactive information gains and visual templates constitute the digital twin through bidirectional data flowing and real-time optimization. As a demonstration of concept, on the conveyor-based and vision-guided robotic grasping platform, the robotic grasping experiments of freely placed and moving parts were performed. Experimental results indicated that the autonomous and real-time optimization of the conveyor-based and vision-guided robotic grasping system happens and the adaptability to the real-world changes had been clearly increased. This research suggested that the representation and dynamic capture of the complex interactions between both sides of cyber-physical system could generate new possibilities to the evolution of decision-making paradigm in more complex industrial processes.     

Robust object manipulation for tactile-based blind grasping

Tactile-based blind grasping addresses realistic robotic grasping in which the hand only has access to proprioceptive and tactile sensors. The robotic hand has no prior knowledge of the object/grasp properties, such as object weight, inertia, and shape. There exists no manipulation controller that rigorously guarantees object manipulation in such a setting. Here, a robust control law is proposed for object manipulation in tactile-based blind grasping. The analysis ensures semi-global asymptotic and exponential stability in the presence of model uncertainties and external disturbances that are neglected in related work. Simulation and hardware results validate the effectiveness of the proposed approach.     

Proposal of a Single-Trocar Assemblable Hand for Laparoscopic Surgery

Large instruments are not suitable for laparoscopic surgery because they cannot pass through trocars, which are typically less than 12 mm in diameter; however, operating on large internal organs with a slender instrument is often difficult. To overcome this limitation, we have proposed an 'assemblable instrument', whose parts are inserted through trocars and assembled inside the abdominal cavity to form a large instrument. We have previously reported the development of assemblable hands that require two trocars for assembly. In this paper, we propose a simple three-fingered hand whose function is limited to retracting or grasping, but whose assembly requires a single trocar. We develop two types of finger units: one for a retracting hand and the other for a grasping hand. The two finger units can be connected to a single main unit of the hand. We conduct in vivo experiments. The retracting hand can retract several large internal organs and lift up the stomach with its three fingers from the bottom. The grasping hand can grasp the spleen stably with its two fingers from the bottom.     

Human-inspired force compliant grasping primitives

We address the problem of grasping everyday objects that are small relative to an anthropomorphic hand, such as pens, screwdrivers, cellphones, and hammers from their natural poses on a support surface, e.g., a table top. In such conditions, state of the art grasp generation techniques fail to provide robust, achievable solutions due to either ignoring or trying to avoid contact with the support surface. In contrast, when people grasp small objects, they often make use of substantial contact with the support surface. In this paper we give results of human subjects grasping studies which show the extent and characteristics of environment contact under different 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 experiments on a variety of small objects with similar shape and size. The results demonstrate that our approach is robust to localization uncertainties and applies to many everyday objects.     

An expert system for design for robotic assembly

In recent years, due to the various advantages associated with automation and robotics, much work has been done in developing robotic systems for assembly operations. Since part design plays a major role in assembly, this paper deals with the design of parts for ease of robotic assembly. Considerable knowledge is available in the form of design for robotic assembly rules. In addition, a large amount of data is required for decisions regarding suitability of parts for robotic assembly. The implementation of design for robotic assembly rules would be much easier with the help of an expert system, which would guide the designer toward choosing the design alternative that can best facilitate ease of assembly from a robotic point of view.To this end, a prototype expert system for design for robotic assembly is developed and presented in this paper. The expert system was implemented as a production system, which consists of rules and Object-Attribute-Value (O-A-V) triplets to represent domain knowledge. In order to best utilize the domain specific knowledge, a state space search-based inference mechanism was employed. The implementation of the prototype system is illustrated with examples.     

State-of-the-Art control strategies for robotic PiH assembly

Nowadays, industrial robots have been widely applied for performing position-controlled tasks with minimum contact such as spot welding, spray painting, packing, and material handling; however, performing high-tolerance assembly tasks still poses a great challenge for robots because of various uncertainties of the parts to be assembled such as fixtures, end effector tools, or axes. From this perspective, the advancement of research and development has led to cutting-edge robotic technologies for industrial applications. To understand the technological trend of industrial robots, investigated the state-of-the-art robotic assembly technologies to identify the limitations of existing works and clarify future research directions in the field. This paper especially interested on typical peg-in-hole (PiH) assemblies, as PiH methods provide insights for further development of robot assemblies. The assembly control strategies for PiH operations is classified by based on the types and features of the assemblies, and the literature in terms of the contributions of these studies is compared to PiH assembly. Finally, the control strategies for robotic PiH assemblies are discussed in detail, and the limitations of the current robotic assembly technologies are discussed to identify the future direction of research for the control of robotic assembly.     

A HUMANLIKE GRASPING FORCE PLANNER FOR OBJECT MANIPULATION BY ROBOT MANIPULATORS

Recently robot manipulators have been expected to perform sophisticated tasks such as object manipulation, assembly tasks, or cooperative tasks with human workers. In order to realize these tasks with robot manipulators, it is important to understand the human strategy of object grasping and manipulation. In this study, we have examined how a human being decides the grasping force necessary to manipulate an unknown object in order to apply human object-grasping strategy for robotic systems. Experiments have been performed with several kinds of objects under several kinds of conditions to investigate how much grasping force human subjects generate. Adjustment strategy of human grasping force when the object is manipulated or in contact with an environment is also examined. Neural networks (the desired grasping force planner) that generate the humanlike desired grasping force are then designed for robotic systems. The effectiveness of the proposed desired grasping force planner is evaluated via experiments.     

A framework for compliant physical interaction

Although the grasp-task interplay in our daily life is unquestionable, very little research has addressed this problem in robotics. In order to fill the gap between the grasp and the task, we adopt the most successful approaches to grasp and task specification, and extend them with additional elements that allow to define a grasp-task link. We propose a global sensor-based framework for the specification and robust control of physical interaction tasks, where the grasp and the task are jointly considered on the basis of the task frame formalism and the knowledge-based approach to grasping. A physical interaction task planner is also presented, based on the new concept of task-oriented hand preshapes. The planner focuses on manipulation of articulated parts in home environments, and is able to specify automatically all the elements of a physical interaction task required by the proposed framework. Finally, several applications are described, showing the versatility of the proposed approach, and its suitability for the fast implementation of robust physical interaction tasks in very different robotic systems.     

The multiple-robot assembly plan problem

In previous research, we defined, classified, and solved the robotic assembly plan problem for a single assembly robot. In this paper, we formulate this problem for the case of multiple, cooperating assembly robots. The problem now includes the allocation of assembly tasks among multiple robots.     

PDE-based robust robotic navigation

In robotic navigation, path planning is aimed at getting the optimum collision-free path between a starting and target locations. The optimality criterion depends on the surrounding environment and the running conditions. In this paper, we propose a general, robust, and fast path planning framework for robotic navigation using level set methods. A level set speed function is proposed such that the minimum cost path between the starting and target locations in the environment, is the optimum planned path. The speed function is controlled by one parameter, which takes one of three possible values to generate either the safest, the shortest, or the hybrid planned path. The hybrid path is much safer than the shortest path, but less shorter than the safest one. The main idea of the proposed technique is to propagate a monotonic wave front with a particular speed function from a starting location until the target is reached and then extracts the optimum planned path between them by solving an ordinary differential equation (ODE) using an efficient numerical scheme. The framework supports both local and global planning for both 2D and 3D environments. The robustness of the proposed framework is demonstrated by correctly extracting planned paths of complex maps.     

虚拟手抓持规则融合策略研究

群体虚拟手抓持规则是虚拟手和虚拟物体进行抓持操作的交互规则,用于判定虚拟手是否能够成功抓持物体。对基于几何的虚拟手抓持规则和基于物理的虚拟手抓持规则分别进行了研究,针对基于几何的虚拟手抓持规则规则简单、仿真效果较差,基于物理模型的虚拟手抓持规则计算复杂、难以实现实时仿真的问题:（1）改进基于几何的虚拟手抓持规则,通过接触点位置、法矢和抓持面法矢制定抓持规则,使其效果逼近力封闭虚拟手抓持规则;（2）利用力封闭计算中抓持接触点和法矢不变的特性,通过内力配比避免了抓持操作中的非线性规划求解,使抓持操作阶段实现实时仿真;（3）通过几何约束进行初始抓持判断-力封闭计算校正-内力配比力封闭计算的策略,实现了完整的抓持过程实时仿真。设计的交互实验说明该抓持规则能实现高沉浸感和实时性的抓持仿真,可以应用到虚拟训练、虚拟装配等仿真平台。     

Task-based compliance planning for multi-fingered robotic manipulations

Based on the analysis of the stiffness relation between the operational space and the fingertip space of multi-fingered hands, this paper provides a guideline of task-based compliance planning for multi-fingered robotic manipulations. In order to show the characteristics of the taskbased stiffness matrix, various two- and three-dimensional examples are illustrated. Also, it is shown that some of the coupling stiffness elements cannot be planned arbitrarily due to grasping geometry. Through the analytical results, it is concluded that the operational stiffness matrix should be carefully specified by considering the location of the compliance center and the grasp geometry of multifingered hands for successful grasping and manipulation tasks.     

Design and Implementation of a Low Cost Multi-Fingered Robotic Hand Using a Method of Blocks

The control of a mechanical robotic hand is plagued by an inability to derive accurate dynamic models of such a mechanism. The aspects of static and kinetic friction are major obstacles in the control of a mechanical hand. This paper presents a fuzzy-like based controller and its implementation for a low cost robotic hand. The controller has the ability to automatically regenerate the member set during the translation of any arbitrary joint in a robotic hand. A series of simulations has been conducted that illustrate the effectiveness of this controller for providing smooth translation independent of frictional forces.The implementation of the controller used here is based on an IBM compatible computer using a custom designed acquisition/conversion interface and a mechanical hand assembly. A hand with a progressively linked finger structure has been used for simplicity. The acquisition system used here allows bidirectional communication with the sensors and actuators of the hand.A series of experiments have been conducted which verify that the method of blocks was successful for controlling joint position. The simulation results include both fine movements, needed for dexterity, and gross movements that can be used for grasping. This robotic hand produces good results in a low cost implementation.