Folding Assembly by Means of Dual-Arm Robotic Manipulation

In this paper, we consider folding assembly as an assembly primitive suitable for dual-arm robotic assembly, that can be integrated in a higher level assembly strategy. The system composed by two pieces in contact is modelled as an articulated object, connected by a prismatic-revolute joint. Different grasping scenarios were considered in order to model the system, and a simple controller based on feedback linearisation is proposed, using force torque measurements to compute the contact point kinematics. The folding assembly controller has been experimentally tested with two sample parts, in order to showcase folding assembly as a viable assembly primitive.Comment: 7 pages, accepted for ICRA 201

Kinematic Analysis of Multi-Fingered, Anthropomorphic Robotic Hands

The ability of stable grasping and fine manipulation with the multi-fingered robot hand with required precision and dexterity is playing an increasingly important role in the applications like service robots, rehabilitation, humanoid robots, entertainment robots, industries etc.. A number of multi-fingered robotic hands have been developed by various researchers in the past. The distinct advantages of a multi-fingered robot hand having structural similarity with human hand motivate the need for an anthropomorphic robot hand. Such a hand provides a promising base for supplanting human hand in execution of tedious, complicated and dangerous tasks, especially in situations such as manufacturing, space, undersea etc. These can also be used in orthopaedic rehabilitation of humans for improving the quality of the life of people having orthopedically and neurological disabilities. The developments so far are mostly driven by the application requirements. There are a number of bottlenecks with industrial grippers as regards to the stability of grasping objects of irregular geometries or complex manipulation operations. A multi-fingered robot hand can be made to mimic the movements of a human hand. The present piece of research work attempts to conceptualize and design a multi-fingered, anthropomorphic robot hand by structurally imitating the human hand. In the beginning, a brief idea about the history, types of robotic hands and application of multi-fingered hands in various fields are presented. A review of literature based on different aspects of the multi-fingered hand like structure, control, optimization, gasping etc. is made. Some of the important and more relevant literatures are elaborately discussed and a brief analysis is made on the outcomes and shortfalls with respect to multi-fingered hands. Based on the analysis of the review of literature, the research work aims at developing an improved anthropomorphic robot hand model in which apart from the four fingers and a thumb, the palm arch effect of human hand is also considered to increase its dexterity. A robotic hand with five anthropomorphic fingers including the thumb and palm arch effect having 25 degrees-of-freedom in all is investigated in the present work. Each individual finger is considered as an open loop kinematic chain and each finger segment is considered as a link of the manipulator. The wrist of the hand is considered as a fixed point. The kinematic analyses of the model for both forward kinematics and inverse kinematic are carried out. The trajectories of the tip positions of the thumb and the fingers with respect to local coordinate system are determined and plotted. This gives the extreme position of the fingertips which is obtained from the forward kinematic solution with the help of MATLAB. Similarly, varying all the joint iv angles of the thumb and fingers in their respective ranges, the reachable workspace of the hand model is obtained. Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for solving the inverse kinematic problem of the fingers. Since the multi-fingered hand grasps the object mainly through its fingertips and the manipulation of the object is facilitated by the fingers due to their dexterity, the grasp is considered to be force-closure grasp. The grasping theory and different types of contacts between the fingertip and object are presented and the conditions for stable and equilibrium grasp are elaborately discussed. The proposed hand model is simulated to grasp five different shaped objects with equal base dimension and height. The forces applied on the fingertip during grasping are calculated. The hand model is also analysed using ANSYS to evaluate the stresses being developed at various points in the thumb and fingers. This analysis was made for the hand considering two different hand materials i.e. aluminium alloy and structural steel. The solution obtained from the forward kinematic analysis of the hand determines the maximum size for differently shaped objects while the solution to the inverse kinematic problem indicates the configurations of the thumb and the fingers inside the workspace of the hand. The solutions are predicted in which all joint angles are within their respective ranges. The results of the stress analysis of the hand model show that the structure of the fingers and the hand as a whole is capable of handling the selected objects. The robot hand under investigation can be realized and can be a very useful tool for many critical areas such as fine manipulation of objects, combating orthopaedic or neurological impediments, service robotics, entertainment robotics etc. The dissertation concludes with a summary of the contribution and the scope of further work

Robotic Grasping of Large Objects for Collaborative Manipulation

In near future, robots are envisioned to work alongside humans in professional and domestic environments without significant restructuring of workspace. Robotic systems in such setups must be adept at observation, analysis and rational decision making. To coexist in an environment, humans and robots will need to interact and cooperate for multiple tasks. A fundamental such task is the manipulation of large objects in work environments which requires cooperation between multiple manipulating agents for load sharing. Collaborative manipulation has been studied in the literature with the focus on multi-agent planning and control strategies. However, for a collaborative manipulation task, grasp planning also plays a pivotal role in cooperation and task completion. In this work, a novel approach is proposed for collaborative grasping and manipulation of large unknown objects. The manipulation task was defined as a sequence of poses and expected external wrench acting on the target object. In a two-agent manipulation task, the proposed approach selects a grasp for the second agent after observing the grasp location of the first agent. The solution is computed in a way that it minimizes the grasp wrenches by load sharing between both agents. To verify the proposed methodology, an online system for human-robot manipulation of unknown objects was developed. The system utilized depth information from a fixed Kinect sensor for perception and decision making for a human-robot collaborative lift-up. Experiments with multiple objects substantiated that the proposed method results in an optimal load sharing despite limited information and partial observability

Graphical modelling of modular machines

This research is aimed at advancing machine design through specifying and implementing (in "proof of concept" form) a set of tools which graphically model modular machines. The tools allow mechanical building elements (or machine modules) to be selected and configured together in a highly flexible manner so that operation of the chosen configuration can be simulated and performance properties evaluated. Implementation of the tools has involved an extension in capability of a proprietary robot simulation system. This research has resulted in a general approach to graphically modelling manufacturing machines built from modular elements. A focus of study has been on a decomposition of machine functionality leading to the establishment of a library of modular machine primitives. This provides a useful source of commonly required machine building elements for use by machine designers. Study has also focussed on the generation of machine configuration tools which facilitate the construction of a simulation model and ultimately the physical machine itself. Simulation aspects of machine control are also considered which depict methods of manipulating a machine model in the simulation phase. In addition methods of achieving machine programming have been considered which specify the machine and its operational tasks. Means of adopting common information data structures are also considered which can facilitate interfacing with other systems, including the physical machine system constructed as an issue of the simulation phase. Each of these study areas is addressed in its own context, but collectively they provide a means of creating a complete modular machine design environment which can provide significant assistance to machine designers. Part of the methodology employed in the study is based on the use of the discrete event simulation technique. To easily and effectively describe a modular machine and its activity in a simulation model, a hierarchical ring and tree data structure has been designed and implemented. The modularity and reconfigurability are accommodated by the data structure, and homogeneous transformations are adopted to determine the spatial location and orientation of each of the machine elements. A three-level machine task programming approach is used to describe the machine's activities. A common data format method is used to interface the machine design environment with the physical machine and other building blocks of manufacturing systems (such as CAD systems) where systems integration approaches can lead to enhanced product realisation. The study concludes that a modular machine design environment can be created by employing the graphical simulation approach together with a set of comprehensive configuration. tools. A generic framework has been derived which outlines the way in which machine design environments can be constructed and suggestions are made as to how the proof of concept design environment implemented in this study can be advanced

Dynamic modeling and simulation of a multi-fingered robot hand.

by Joseph Chun-kong Chan.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.Includes bibliographical references (leaves 117-124).Abstract also in Chinese.Abstract --- p.iAcknowledgments --- p.ivList of Figures --- p.xiList of Tables --- p.xiiList of Algorithms --- p.xiiiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation --- p.1Chapter 1.2 --- Related Work --- p.5Chapter 1.3 --- Contributions --- p.7Chapter 1.4 --- Organization of the Thesis --- p.9Chapter 2 --- Contact Modeling: Kinematics --- p.11Chapter 2.1 --- Introduction --- p.11Chapter 2.2 --- Contact Kinematics between Two Rigid Bodies --- p.14Chapter 2.2.1 --- Contact Modes --- p.14Chapter 2.2.2 --- Montana's Contact Equations --- p.15Chapter 2.3 --- Finger Kinematics --- p.18Chapter 2.3.1 --- Finger Forward Kinematics --- p.19Chapter 2.3.2 --- Finger Jacobian --- p.21Chapter 2.4 --- Grasp Kinematics between a Finger and an Object --- p.21Chapter 2.4.1 --- Velocity Transformation between Different Coordinate Frames --- p.22Chapter 2.4.2 --- Grasp Kinematics for the zth Contact --- p.23Chapter 2.4.3 --- Different Fingertip Models and Different Contact Modes --- p.25Chapter 2.5 --- Velocity Constraints of the Entire System --- p.28Chapter 2.6 --- Summary --- p.29Chapter 3 --- Contact Modeling: Dynamics --- p.31Chapter 3.1 --- Introduction --- p.31Chapter 3.2 --- Multi-fingered Robot Hand Dynamics --- p.33Chapter 3.3 --- Object Dynamics --- p.35Chapter 3.4 --- Constrained System Dynamics --- p.37Chapter 3.5 --- Summary --- p.39Chapter 4 --- Collision Modeling --- p.40Chapter 4.1 --- Introduction --- p.40Chapter 4.2 --- Assumptions of Collision --- p.42Chapter 4.3 --- Collision Point Velocities --- p.43Chapter 4.3.1 --- Collision Point Velocity of the ith. Finger --- p.43Chapter 4.3.2 --- Collision Point Velocity of the Object --- p.46Chapter 4.3.3 --- Relative Collision Point Velocity --- p.47Chapter 4.4 --- Equations of Collision --- p.47Chapter 4.4.1 --- Sliding Mode Collision --- p.48Chapter 4.4.2 --- Sticking Mode Collision --- p.49Chapter 4.5 --- Summary --- p.51Chapter 5 --- Dynamic Simulation --- p.53Chapter 5.1 --- Introduction --- p.53Chapter 5.2 --- Architecture of the Dynamic Simulation System --- p.54Chapter 5.2.1 --- Input Devices --- p.54Chapter 5.2.2 --- Dynamic Simulator --- p.58Chapter 5.2.3 --- Virtual Environment --- p.60Chapter 5.3 --- Methodologies and Program Flow of the Dynamic Simulator --- p.60Chapter 5.3.1 --- Interference Detection --- p.61Chapter 5.3.2 --- Constraint-based Simulation --- p.63Chapter 5.3.3 --- Impulse-based Simulation --- p.66Chapter 5.4 --- Summary --- p.69Chapter 6 --- Simulation Results --- p.71Chapter 6.1 --- Introduction --- p.71Chapter 6.2 --- Change of Grasping Configurations --- p.71Chapter 6.3 --- Rolling Contact --- p.76Chapter 6.4 --- Sliding Contact --- p.76Chapter 6.5 --- Collisions --- p.85Chapter 6.6 --- Dextrous Manipulation Motions --- p.93Chapter 6.7 --- Summary --- p.94Chapter 7 --- Conclusions --- p.99Chapter 7.1 --- Summary of Contributions --- p.99Chapter 7.2 --- Future Work --- p.100Chapter 7.2.1 --- Improvement of Current System --- p.100Chapter 7.2.2 --- Applications --- p.101Chapter A --- Montana's Contact Equations for Finger-object Contact --- p.103Chapter A.1 --- Local Coordinates Charts --- p.103Chapter A.2 --- "Curvature, Torsion and Metric Tensors" --- p.104Chapter A.3 --- Montana's Contact Equations --- p.106Chapter B --- Finger Dynamics --- p.108Chapter B.1 --- Forward Kinematics of a Robot Finger --- p.108Chapter B.1.1 --- Link-coordinate Transformation --- p.109Chapter B.1.2 --- Forward Kinematics --- p.109Chapter B.2 --- Dynamic Equation of a Robot Finger --- p.110Chapter B.2.1 --- Kinetic and Potential Energy --- p.110Chapter B.2.2 --- Lagrange's Equation --- p.111Chapter C --- Simulation Configurations --- p.113Chapter C.1 --- Geometric models --- p.113Chapter C.2 --- Physical Parameters --- p.113Chapter C.3 --- Simulation Parameters --- p.116Bibliography --- p.12

A Posture Sequence Learning System for an Anthropomorphic Robotic Hand

The paper presents a cognitive architecture for posture learning of an anthropomorphic robotic hand. Our approach is aimed to allow the robotic system to perform complex perceptual operations, to interact with a human user and to integrate the perceptions by a cognitive representation of the scene and the observed actions. The anthropomorphic robotic hand imitates the gestures acquired by the vision system in order to learn meaningful movements, to build its knowledge by different conceptual spaces and to perform complex interaction with the human operator

Manipulation Planning for Forceful Human-Robot-Collaboration

This thesis addresses the problem of manipulation planning for forceful human-robot collaboration. Particularly, the focus is on the scenario where a human applies a sequence of changing external forces through forceful operations (e.g. cutting a circular piece off a board) on an object that is grasped by a cooperative robot. We present a range of planners that 1) enable the robot to stabilize and position the object under the human applied forces by exploiting supports from both the object-robot and object-environment contacts; 2) improve task efficiency by minimizing the need of configuration and grasp changes required by the changing external forces; 3) improve human comfort during the forceful interaction by optimizing the defined comfort criteria. We first focus on the instance of using only robotic grasps, where the robot is supposed to grasp/regrasp the object multiple times to keep it stable under the changing external forces. We introduce a planner that can generate an efficient manipulation plan by intelligently deciding when the robot should change its grasp on the object as the human applies the forces, and choosing subsequent grasps such that they minimize the number of regrasps required in the long-term. The planner searches for such an efficient plan by first finding a minimal sequence of grasp configurations that are able to keep the object stable under the changing forces, and then generating connecting trajectories to switch between the planned configurations, i.e. planning regrasps. We perform the search for such a grasp (configuration) sequence by sampling stable configurations for the external forces, building an operation graph using these stable configurations and then searching the operation graph to minimize the number of regrasps. We solve the problem of bimanual regrasp planning under the assumption of no support surface, enabling the robot to regrasp an object in the air by finding intermediate configurations at which both the bimanual and unimanual grasps can hold the object stable under gravity. We present a variety of experiments to show the performance of our planner, particularly in minimizing the number of regrasps for forceful manipulation tasks and planning stable regrasps. We then explore the problem of using both the object-environment contacts and object-robot contacts, which enlarges the set of stable configurations and thus boosts the robot’s capability in stabilizing the object under external forces. We present a planner that can intelligently exploit the environment’s and robot’s stabilization capabilities within a unified planning framework to search for a minimal number of stable contact configurations. A big computational bottleneck in this planner is due to the static stability analysis of a large number of candidate configurations. We introduce a containment relation between different contact configurations, to efficiently prune the stability checking process. We present a set of real-robot and simulated experiments illustrating the effectiveness of the proposed framework. We present a detailed analysis of the proposed containment relationship, particularly in improving the planning efficiency. We present a planning algorithm to further improve the cooperative robot behaviour concerning human comfort during the forceful human-robot interaction. Particularly, we are interested in empowering the robot with the capability of grasping and positioning the object not only to ensure the object stability against the human applied forces, but also to improve human experience and comfort during the interaction. We address human comfort as the muscular activation level required to apply a desired external force, together with the human spatial perception, i.e. the so-called peripersonal-space comfort during the interaction. We propose to maximize both comfort metrics to optimize the robot and object configuration such that the human can apply a forceful operation comfortably. We present a set of human-robot drilling and cutting experiments which verify the efficiency of the proposed metrics in improving the overall comfort and HRI experience, without compromising the force stability. In addition to the above planning work, we present a conic formulation to approximate the distribution of a forceful operation in the wrench space with a polyhedral cone, which enables the planner to efficiently assess the stability of a system configuration even in the presence of force uncertainties that are inherent in the human applied forceful operations. We also develop a graphical user interface, which human users can easily use to specify various forceful tasks, i.e. sequences of forceful operations on selected objects, in an interactive manner. The user interface ties in human task specification, on-demand manipulation planning and robot-assisted fabrication together. We present a set of human-robot experiments using the interface demonstrating the feasibility of our system. In short, in this thesis we present a series of planners for object manipulation under changing external forces. We show the object contacts with the robot and the environment enable the robot to manipulate an object under external forces, while making the most of the object contacts has the potential to eliminate redundant changes during manipulation, e.g. regrasp, and thus improve task efficiency and smoothness. We also show the necessity of optimizing human comfort in planning for forceful human-robot manipulation tasks. We believe the work presented here can be a key component in a human-robot collaboration framework

Grasp planning for object manipulation by an autonomous robot

L'évolution autonome d'un robot dans un environnement évolutif nécessite qu'il soit doté de capacités de perception, d'action et de décision suffisantes pour réaliser la tâche assignée. Une tâche essentielle en robotique est la manipulation d'objets et d'outils. Elle intervient non seulement pour un robot seul mais également dans des situations d'interaction avec un humain ou un autre robot quand il s’agit d’échanger des objets ou de les manipuler conjointement.\ud Cette thèse porte sur la planification de tâches de manipulation d'objets pour un robot autonome dans un environnement humain. Une architecture logicielle susceptible de résoudre ce type de problèmes au niveau géométrique est proposée. Généralement, une tâche de manipulation commence par une opération de saisie dont la qualité conditionne fortement la réussite de la tâche et pour laquelle nous proposons un planificateur basé sur les propriétés inertielles de l'objet et une décomposition en éléments quasi-convexes tout en prenant en compte les contraintes imposées par le système mobile complet dans un environnement donné.\ud Les résultats sont validés en simulation et sur le robot sur la base d’une extension des outils de planification développés au LAAS-CNRS. Le modèle géométrique 3D de l’objet peut être connu a priori ou bien acquis en ligne. Des expérimentations menées sur un robot manipulateur mobile équipé d'une pince à trois points de contacts, de capteurs de force et d'une paire de caméras stéréoscopiques ont montré la validité de l'approche.\ud The autonomous robot performance in a dynamic environment requires advanced perception, action and decision capabilities. Interaction with the environment plays a key role for a robot and it is well illustrated in object and/or tool manipulation. Interaction with humans or others robots can consist in object exchanges.\ud This thesis deals with object manipulation planning by an autonomous robot in human environments. A software architecture is proposed that is capable to solve such problems at the geometrical level. In general, a manipulation task starts by a grasp operation which quality influences strongly the success of the overall task. We propose a planner based on object inertial properties and an approximate convex decomposition. The whole mobile system taken into account in the planning process.\ud The planner has been completely implemented as an extension of the planning tools developed at LAAS-CNRS. Its results have been tested in simulation and on a robotic platform. Object models may be known a priori or acquired on-line. Experiments have been carried out with a mobile manipulator equipped with a three fingers gripper, a wrist force sensor and a stereo camera system in order to validate the approach.\ud \ud \u

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 344)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during January, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Physical human-robot collaboration: Robotic systems, learning methods, collaborative strategies, sensors, and actuators

This article presents a state-of-the-art survey on the robotic systems, sensors, actuators, and collaborative strategies for physical human-robot collaboration (pHRC). This article starts with an overview of some robotic systems with cutting-edge technologies (sensors and actuators) suitable for pHRC operations and the intelligent assist devices employed in pHRC. Sensors being among the essential components to establish communication between a human and a robotic system are surveyed. The sensor supplies the signal needed to drive the robotic actuators. The survey reveals that the design of new generation collaborative robots and other intelligent robotic systems has paved the way for sophisticated learning techniques and control algorithms to be deployed in pHRC. Furthermore, it revealed the relevant components needed to be considered for effective pHRC to be accomplished. Finally, a discussion of the major advances is made, some research directions, and future challenges are presented