Control of an Anthropomorphic Arm-hand Robot for Grasping and Dexterous Manipulation

Control of an Anthropomorphic Arm-hand Robot for Grasping and Dexterous Manipulation
Author: Kien Cuong Nguyen
Publisher:
Total Pages: 159
Release: 2013
Genre:
ISBN:

This thesis deals with the control of an anthropomorphic arm-hand robot by focusing on two aspects: the control of the fingertip force and the coordination between the arm and the hand. The force control of a robotic finger remains difficult despite the advances in current state-of-art. This is due to the small size of the finger, its low communication bandwidth, the lack of precision of the position sensors and the significant backlash in the actuation systems. A new approach controlling the fingertip force by adjusting the joint torque saturation parameter shows better results. Not limited to pure force control, this control method is proved to also have good performance when applying to indirect and hybrid position/force control. Usually ignored in literature while considering dexterous manipulation, the position and movement of the arm play a very important role. Many in-hand manipulation tasks cannot be realized without a proper movement of the arm. One typical example is the rotation of the manipulated object relative to the palm without moving the fingers thanks to inertial and gravitational effects. Besides, arm movement is also an important factor contributing to the appearance of the grasping gestures. In this thesis, the movement of the grasped object under gravitational effect was analyzed and a grasping strategy was elaborated. In addition to this, some mechanical constraints (tenodesis effect in particular) contributing to the human natural gestures were deciphered and such natural gestures were reproduced on an anthropomorphic arm-hand robot in redundant grasping situations.

Human Inspired Dexterity in Robotic Manipulation

Human Inspired Dexterity in Robotic Manipulation
Author: Tetsuyou Watanabe
Publisher: Academic Press
Total Pages: 220
Release: 2018-06-26
Genre: Technology & Engineering
ISBN: 0128133961

Human Inspired Dexterity in Robotic Manipulation provides up-to-date research and information on how to imitate humans and realize robotic manipulation. Approaches from both software and hardware viewpoints are shown, with sections discussing, and highlighting, case studies that demonstrate how human manipulation techniques or skills can be transferred to robotic manipulation. From the hardware viewpoint, the book discusses important human hand structures that are key for robotic hand design and how they should be embedded for dexterous manipulation. This book is ideal for the research communities in robotics, mechatronics and automation. Investigates current research direction in robotic manipulation Shows how human manipulation techniques and skills can be transferred to robotic manipulation Identifies key human hand structures for robotic hand design and how they should be embedded in the robotic hand for dexterous manipulation

Advanced Bimanual Manipulation

Advanced Bimanual Manipulation
Author: Bruno Siciliano
Publisher: Springer
Total Pages: 284
Release: 2012-04-10
Genre: Technology & Engineering
ISBN: 3642290418

Dexterous and autonomous manipulation is a key technology for the personal and service robots of the future. Advances in Bimanual Manipulation edited by Bruno Siciliano provides the robotics community with the most noticeable results of the four-year European project DEXMART (DEXterous and autonomous dual-arm hand robotic manipulation with sMART sensory-motor skills: A bridge from natural to artificial cognition). The volume covers a host of highly important topics in the field, concerned with modelling and learning of human manipulation skills, algorithms for task planning, human-robot interaction, and grasping, as well as hardware design of dexterous anthropomorphic hands. The results described in this five-chapter collection are believed to pave the way towards the development of robotic systems endowed with dexterous and human-aware dual-arm/hand manipulation skills for objects, operating with a high degree of autonomy in unstructured real-world environments.

In-Hand Object Localization and Control: Enabling Dexterous Manipulation with Robotic Hands

In-Hand Object Localization and Control: Enabling Dexterous Manipulation with Robotic Hands
Author: Martin Pfanne
Publisher: Springer Nature
Total Pages: 213
Release: 2022-08-31
Genre: Technology & Engineering
ISBN: 3031069676

This book introduces a novel model-based dexterous manipulation framework, which, thanks to its precision and versatility, significantly advances the capabilities of robotic hands compared to the previous state of the art. This is achieved by combining a novel grasp state estimation algorithm, the first to integrate information from tactile sensing, proprioception and vision, with an impedance-based in-hand object controller, which enables leading manipulation capabilities, including finger gaiting. The developed concept is implemented on one of the most advanced robotic manipulators, the DLR humanoid robot David, and evaluated in a range of challenging real-world manipulation scenarios and tasks. This book greatly benefits researchers in the field of robotics that study robotic hands and dexterous manipulation topics, as well as developers and engineers working on industrial automation applications involving grippers and robotic manipulators.

Neuro-Fuzzy Grasp Control for a Teleoperated Five Finger Anthropomorphic Robotic Hand

Neuro-Fuzzy Grasp Control for a Teleoperated Five Finger Anthropomorphic Robotic Hand
Author: Maxwell Joseph Welyhorsky
Publisher:
Total Pages:
Release: 2021
Genre:
ISBN:

Robots should offer a human-like level of dexterity when handling objects if humans are to be replaced in dangerous and uncertain working environments. This level of dexterity for human-like manipulation must come from both the hardware, and the control. Exact replication of human-like degrees of freedom in mobility for anthropomorphic robotic hands are seen in bulky, costly, fully actuated solutions, while machine learning to apply some level of human-like dexterity in underacted solutions is unable to be applied to a various array of objects. This thesis presents experimental and theoretical contributions of a novel neuro-fuzzy control method for dextrous human grasping based on grasp synergies using a Human Computer Interface glove and upgraded haptic-enabled anthropomorphic Ring Ada dexterous robotic hand. Experimental results proved the efficiency of the proposed Adaptive Neuro-Fuzzy Inference Systems to grasp objects with high levels of accuracy.

Teleoperated Grasping Using an Upgraded Haptic-Enabled Human-Like Robotic Hand and a CyberTouch Glove

Teleoperated Grasping Using an Upgraded Haptic-Enabled Human-Like Robotic Hand and a CyberTouch Glove
Author: Qi Zhu
Publisher:
Total Pages:
Release: 2020
Genre:
ISBN:

Grasping, the skill to hold objects and tools while doing in-hand manipulation, still is in many cases an unsolvable problem for robotics, but a natural act for humans. An efficient grasping requires not only human-like robotic hands with articulated fingers but also tactile, force, and kinesthetic sensors for the precise control of the forces and motions exerted during the manipulation. As a fully autonomous robotic dexterous manipulation is too difficult to develop for changing and unstructured environments, an alternative approach is to combine the low-level robot computer control with the higher-level perception and task planning abilities of a human operator equipped with an adequate human-computer interface (HCI). This thesis presents theoretical and experimental contributions to the development of an upgraded haptic-enabled anthropomorphic Ring Ada dexterous robotic hand and a biology-inspired synergistic real-time control system for teleoperated grasping of different objects using a CyberTouch HCI data glove. A fuzzy logic controller module was developed to efficiently control the underactuated Ring Ada' robotic hand during grasping. A machine learning classification system was developed to recognize grasped objects. Experiments have convincingly demonstrated that our novel Ring Ada robotic hand equipped with kinematic position sensors and touch sensors is able to efficiently grasp different lightweight objects through teleoperation.

Dextrous Robot Hands

Dextrous Robot Hands
Author: Subramanian T. Venkataraman
Publisher: Springer Science & Business Media
Total Pages: 349
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 1461389747

Manipulation using dextrous robot hands has been an exciting yet frustrating research topic for the last several years. While significant progress has occurred in the design, construction, and low level control of robotic hands, researchers are up against fundamental problems in developing algorithms for real-time computations in multi-sensory processing and motor control. The aim of this book is to explore parallels in sensorimotor integration in dextrous robot and human hands, addressing the basic question of how the next generation of dextrous hands should evolve. By bringing together experimental psychologists, kinesiologists, computer scientists, electrical engineers, and mechanical engineers, the book covers topics that range from human hand usage in prehension and exploration, to the design and use of robotic sensors and multi-fingered hands, and to control and computational architectures for dextrous hand usage. While the ultimate goal of capturing human hand versatility remains elusive, this book makes an important contribution to the design and control of future dextrous robot hands through a simple underlying message: a topic as complex as dextrous manipulation would best be addressed by collaborative, interdisciplinary research, combining high level and low level views, drawing parallels between human studies and analytic approaches, and integrating sensory data with motor commands. As seen in this text, success has been made through the establishment of such collaborative efforts. The future will hold up to expectations only as researchers become aware of advances in parallel fields and as a common vocabulary emerges from integrated perceptions about manipulation.

Robotic Grasping and Fine Manipulation

Robotic Grasping and Fine Manipulation
Author: M. R. Cutkosky
Publisher: Springer
Total Pages: 200
Release: 1985-08-31
Genre: Computers
ISBN:

When a person picks up a metal part and clamps it in the chuck of a lathe, he begins with his arm, proceeds with his wrist and finishes with his fingers. The arm brings the part near the chuck. The wrist positions the part, giving it the proper orientation to slide in. After the part is inserted, the wrist and fingers make tiny corrections to ensure that it is correctly seated. Today's robot attempting the same operations is at a grave disadvantage if it has to make all motions with the arm. The following work investigates the use of robotic wrists and hands to help industrial robots perform the fine motions needed in a metal working cell. Chapters 1 and 2 are an introduction to the field and a review of previous investigations on related subjects. Little work has been done on grasping and fine manipulation with a robot hand or wrist, but the related subjects of robot arm dynamics and control have an extensive literature.

Approaching Human Performance

Approaching Human Performance
Author: Markus Grebenstein
Publisher: Springer
Total Pages: 234
Release: 2014-01-24
Genre: Technology & Engineering
ISBN: 3319035932

Humanoid robotics have made remarkable progress since the dawn of robotics. So why don't we have humanoid robot assistants in day-to-day life yet? This book analyzes the keys to building a successful humanoid robot for field robotics, where collisions become an unavoidable part of the game. The author argues that the design goal should be real anthropomorphism, as opposed to mere human-like appearance. He deduces three major characteristics to aim for when designing a humanoid robot, particularly robot hands: - Robustness against impacts - Fast dynamics - Human-like grasping and manipulation performance Instead of blindly copying human anatomy, this book opts for a holistic design methodology. It analyzes human hands and existing robot hands to elucidate the important functionalities that are the building blocks toward these necessary characteristics. They are the keys to designing an anthropomorphic robot hand, as illustrated in the high performance anthropomorphic Awiwi Hand presented in this book. This is not only a handbook for robot hand designers. It gives a comprehensive survey and analysis of the state of the art in robot hands as well as the human anatomy. It is also aimed at researchers and roboticists interested in the underlying functionalities of hands, grasping and manipulation. The methodology of functional abstraction is not limited to robot hands, it can also help realize a new generation of humanoid robots to accommodate a broader spectrum of the needs of human society.

High-level Planning of Dexterous In-hand Manipulation Using a Robotic Hand

High-level Planning of Dexterous In-hand Manipulation Using a Robotic Hand
Author: Urbain Prieur
Publisher:
Total Pages: 148
Release: 2013
Genre:
ISBN:

This work considers a robot equipped with an anthropomorphic hand and aims at providing it with efficient autonomous in-hand manipulation skills. While fine in-hand action planning algorithms have interesting state-of-the-art solutions, we built a competitive high-level control layer to plan the complete in-hand manipulation activity. Our solution generates a sequence of subgoals from an initial to a final configuration provided by the task, thus decomposing in-hand manipulation into simple transitions that can be easily planned by the low-level algorithms. We use a Markov decision process (MDP) to generate the sequence, taking into account the object influence and the desired final subgoal. We use a simple state representation for the sugoals: canonical grasp types from a taxonomy, enabling fast and on-line computation. The transitions between grasp types are modelled as probabilities of success. The simple formulation of the sequence leaves the complete configurations and transitions to be planned by the low-level layer, which can ask for a different subgoal path if required. The MDP can generate the appropriate behaviour if the in-hand action skills of the robot are known. They can be learnt by self-exploration of the robot if possible. Otherwise, the behaviour can be directly learnt from human demonstration. We boost the learning process using an empirical guess of the transition probabilities and an active learning algorithm. We implemented our solution on a real platform. The planning of in-hand manipulation relies on the grasp sequence generated which probability of success is used as an insight of the task achievability for the initial grasp choice.