An Optimization Approach to Teleoperation of the Thumb of a Humanoid Robot Hand: Kinematic Mapping and Calibration

2014 ◽  
Vol 136 (9) ◽  
Author(s):  
Lei Cui ◽  
Ugo Cupcic ◽  
Jian S. Dai
Keyword(s):  
Input Device ◽  
Human Hand ◽  
Optimization Approach ◽  
Robotic Hand ◽  
Kinematic Structure ◽  
Robotic Hands ◽  
Data Glove ◽  
Minimax Algorithms ◽  
Kinematic Mapping ◽  
And Control

The complex kinematic structure of a human thumb makes it difficult to capture and control the thumb motions. A further complication is that mapping the fingertip position alone leads to inadequate grasping postures for current robotic hands, many of which are equipped with tactile sensors on the volar side of the fingers. This paper aimed to use a data glove as the input device to teleoperate the thumb of a humanoid robotic hand. An experiment protocol was developed with only minimum hardware involved to compensate for the differences in kinematic structures between a robotic hand and a human hand. A nonlinear constrained-optimization formulation was proposed to map and calibrate the motion of a human thumb to that of a robotic thumb by minimizing the maximum errors (minimax algorithms) of fingertip position while subject to the constraint of the normals of the surfaces of the thumb and the index fingertips within a friction cone. The proposed approach could be extended to other teleoperation applications, where the master and slave devices differ in kinematic structure.

An Affordable Linkage-and-Tendon Hybrid-Driven Anthropomorphic Robotic Hand—MCR-Hand II

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Haosen Yang ◽  
Guowu Wei ◽  
Lei Ren ◽  
Zhihui Qian ◽  
Kunyang Wang ◽  
...  
Keyword(s):  
System Integration ◽  
Mechanical Design ◽  
Low Cost ◽  
Score Test ◽  
Human Hand ◽  
Robotic Hand ◽  
Level Control ◽  
Robotic Hands ◽  
Driven Systems ◽  
And Control

Abstract This paper presents the design, analysis, and development of an anthropomorphic robotic hand coined MCR-hand II. This hand takes the advantages of both the tendon-driven and linkage-driven systems, leading to a compact mechanical structure that aims to imitate the mobility of a human hand. Based on the investigation of the human hand anatomical structure and the related existing robotic hands, mechanical design of the MCR-hand II is presented. Then, using D-H convention, kinematics of this hand is formulated and illustrated with numerical simulations. Furthermore, fingertip force is deduced and analyzed, and mechatronic system integration and control strategy are addressed. Subsequently, a prototype of the proposed robotic hand is developed, integrated with low-level control system, and following which empirical study is carried out, which demonstrates that the proposed hand is capable of implementing the grasp and manipulation of most of the objects used in daily life. In addition, the three widely used tools, i.e., the Kapandji score test, Cutkosky taxonomy, and Kamakura taxonomy, are used to evaluate the performance of the hand, which evidences that the MCR-hand II possesses high dexterity and excellent grasping capability; object manipulation performance is also demonstrated. This paper hence presents the design and development of a type of novel tendon–linkage-integrated anthropomorphic robotic hand, laying broader background for the development of low-cost robotic hands for both industrial and prosthetic use.

On the design of robotic hands for brain–machine interface

2006 ◽  
Vol 20 (5) ◽  
pp. 1-9 ◽  
Author(s):  
Yoky Matsuoka ◽  
Pedram Afshar ◽  
Michael Oh
Keyword(s):  
Brain Machine Interface ◽  
Human Hand ◽  
Prosthetic Hand ◽  
Robotic Hand ◽  
Neural Signals ◽  
Robotic Hands ◽  
Intimate Contact ◽  
Machine Interface ◽  
Optimal Approach ◽  
And Control

✓ Brain–machine interface (BMI) is the latest solution to a lack of control for paralyzed or prosthetic limbs. In this paper the authors focus on the design of anatomical robotic hands that use BMI as a critical intervention in restorative neurosurgery and they justify the requirement for lower-level neuromusculoskeletal details (relating to biomechanics, muscles, peripheral nerves, and some aspects of the spinal cord) in both mechanical and control systems. A person uses his or her hands for intimate contact and dexterous interactions with objects that require the user to control not only the finger endpoint locations but also the forces and the stiffness of the fingers. To recreate all of these human properties in a robotic hand, the most direct and perhaps the optimal approach is to duplicate the anatomical musculoskeletal structure. When a prosthetic hand is anatomically correct, the input to the device can come from the same neural signals that used to arrive at the muscles in the original hand. The more similar the mechanical structure of a prosthetic hand is to a human hand, the less learning time is required for the user to recreate dexterous behavior. In addition, removing some of the nonlinearity from the relationship between the cortical signals and the finger movements into the peripheral controls and hardware vastly simplifies the needed BMI algorithms. (Nonlinearity refers to a system of equations in which effects are not proportional to their causes. Such a system could be difficult or impossible to model.) Finally, if a prosthetic hand can be built so that it is anatomically correct, subcomponents could be integrated back into remaining portions of the user's hand at any transitional locations. In the near future, anatomically correct prosthetic hands could be used in restorative neurosurgery to satisfy the user's needs for both aesthetics and ease of control while also providing the highest possible degree of dexterity.

Transforming Human Hand Motion for Telemanipulation

1992 ◽  
Vol 1 (1) ◽  
pp. 63-79 ◽  
Author(s):  
Thomas H. Speeter
Keyword(s):  
Force Feedback ◽  
Robotic Manipulation ◽  
Human Hand ◽  
Robotic Hand ◽  
Robotic Hands ◽  
Automated Control ◽  
Functional Transformation ◽  
Hand Motion ◽  
Computationally Expensive ◽  
Human Hands

Manipulation by teleoperation (telemanipulation) offers an apparently straightforward and less computationally expensive route toward dextrous robotic manipulation than automated control of multifingered robotic hands. The functional transformation of human hand motions into equivalent robotic hand motions, however, presents both conceptual and analytical problems. This paper reviews and proposes algorithmic methods for transforming the actions of human hands into equivalent actions of slave multifingered robotic hands. Forward positional transformation is considered only, the design of master devices, feedforward dynamics, and force feedback are not considered although their importance for successful telemanipulation is understood. Linear, nonlinear, and functional mappings are discussed along with performance and computational considerations.

scholarly journals Magnetic Array Assisted Triboelectric Nanogenerator Sensor for Real-Time Gesture Interaction

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Ken Qin ◽  
Chen Chen ◽  
Xianjie Pu ◽  
Qian Tang ◽  
Wencong He ◽  
...  
Keyword(s):  
Real Time ◽  
Signal Amplitude ◽  
Human Hand ◽  
Triboelectric Nanogenerator ◽  
Robotic Hand ◽  
Robotic Hands ◽  
Human Machine Interaction ◽  
Gesture Interaction ◽  
New Strategy ◽  
Machine Interaction

AbstractIn human-machine interaction, robotic hands are useful in many scenarios. To operate robotic hands via gestures instead of handles will greatly improve the convenience and intuition of human-machine interaction. Here, we present a magnetic array assisted sliding triboelectric sensor for achieving a real-time gesture interaction between a human hand and robotic hand. With a finger’s traction movement of flexion or extension, the sensor can induce positive/negative pulse signals. Through counting the pulses in unit time, the degree, speed, and direction of finger motion can be judged in real-time. The magnetic array plays an important role in generating the quantifiable pulses. The designed two parts of magnetic array can transform sliding motion into contact-separation and constrain the sliding pathway, respectively, thus improve the durability, low speed signal amplitude, and stability of the system. This direct quantization approach and optimization of wearable gesture sensor provide a new strategy for achieving a natural, intuitive, and real-time human-robotic interaction.

Kinematic Mapping and Calibration of the Thumb Motions for Teleoperating a Humanoid Robot Hand

2011 ◽  
Author(s):  
Lei Cui ◽  
Ugo Cupcic ◽  
Jian S. Dai
Keyword(s):  
Humanoid Robot ◽  
Index Finger ◽  
Input Device ◽  
Human Hand ◽  
Robot Hand ◽  
Optimization Formulation ◽  
Kinematic Mapping ◽  
Dexterous Hand ◽  
Tip Position ◽  
Hand Pose

Mapping and calibration from a human hand to a robot hand pose a challenge due to their differences in kinematic structures. This paper uses the CyberGlove® as the input device for telemanipulating an object with the thumb and the index finger of the Shadow® Dexterous Hand™, with the focus not only on the position but also on the orientation of the thumb fingertip because it is found through experiments conducted on the Shadow Hand that the calibration of tip position alone can lead to unacceptable grasping postures. This paper develops an experiment protocol and proposes a nonlinear optimization formulation that makes the normals of the surfaces of the thumb and index fingertips within the friction cone while subject to fingertip position constraint. The results are verified to be accurate enough to conduct the telemanipulation.

Development and control of a multifingered robotic hand using a pneumatic tendon-driven actuator

2011 ◽  
Vol 23 (3) ◽  
pp. 345-352 ◽  
Author(s):  
Jun-Ya Nagase ◽  
Norihiko Saga ◽  
Toshiyuki Satoh ◽  
Koichi Suzumori
Keyword(s):  
Control System ◽  
Silicone Rubber ◽  
Japanese Population ◽  
Human Hand ◽  
Robotic Hand ◽  
Robot Hand ◽  
Young Workers ◽  
Robot Hands ◽  
Soft Objects ◽  
And Control

Because of the rapid aging of the Japanese population and the acute decrease in young workers in Japan, robots are anticipated for use in performing rehabilitation and daily domestic tasks for nursing and welfare services. Use in environments with humans, safety, and human affinity are particularly important robot hand characteristics. Such robot hands must have flexible movements and be lightweight. Under these circumstances, this study specifically addresses the expansion of a silicone rubber, tendon-driven actuator, which has been developed using a pneumatic balloon. A multifingered robotic hand using the actuator is developed. Moreover, a fuzzy grasping control system is applied to the proposed robotic hand. The robot hand’s development is described incorporating pneumatic balloon actuator with the softness, size, and weight of a human hand. The fuzzy grasping control system is shown to be effective for the proposed robot hand, which can grasp soft objects easily.

Anthropometric Robotic Hand for Pressurized Glove Torque Measurement

2014 ◽  
Vol 11 (02) ◽  
pp. 1450018 ◽  
Author(s):  
Dustyn P. Roberts ◽  
Jack Poon ◽  
Daniella Patrick ◽  
Joo H. Kim
Keyword(s):  
Low Cost ◽  
Human Hand ◽  
Neutral Position ◽  
Robotic Hand ◽  
Robotic Hands ◽  
Performance Requirements ◽  
Transverse Arch ◽  
Data Processing Method ◽  
Design And Testing ◽  
Different Levels

While robotic hands have been developed for tasks such as manipulation and grasping, their potential as tools for evaluation of engineered products — particularly compliant structures that are not easily modeled — has not been broadly studied. In this research, a low-cost anthropometric robotic hand is introduced that is designed to characterize glove stiffness in a pressurized environment. The interaction with the compliant pressurized glove provides unique performance requirements and design constraints. The anthropometric robotic hand was designed to mimic the human hand in a configuration corresponding to the neutral position in zero gravity, including the transverse arch, longitudinal arch, and oblique flexion of the rays. The resulting robotic hand also allows for realistic donning and doffing of the prototype glove, its pressurization, and torque testing of individual joints. Solid modeling and 3D printing enabled the rapid design iterations necessary to work successfully with the compliant pressure garment. An instrumentation and data processing method was used to calculate the required actuator torque at each finger's knuckle joint. The performance of the robotic hand was experimentally demonstrated with a prototype spacesuit glove at different levels of pressure, followed by a statistical repeatability analysis. The reliable measurement method validated the pressure-induced stiffening. The resulting robotic design and testing method provide an objective and systematic way of evaluating the performance of compliant gloves.

scholarly journals Design of a Single-Material Complex Structure Anthropomorphic Robotic Hand

Micromachines ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1124
Author(s):  
Li Tian ◽  
Jianmin Zheng ◽  
Nadia Magnenat Thalmann ◽  
Hanhui Li ◽  
Qifa Wang ◽  
...  
Keyword(s):  
3D Model ◽  
Complex Structure ◽  
Single Type ◽  
Human Hand ◽  
Robotic Hand ◽  
Soft Body ◽  
Robotic Hands ◽  
New Approach ◽  
Motion Range ◽  
Single Material

In the field of robotic hand design, soft body and anthropomorphic design are two trends with a promising future. Designing soft body anthropomorphic robotic hands with human-like grasping ability, but with a simple and reliable structure, is a challenge that still has not been not fully solved. In this paper, we present an anatomically correct robotic hand 3D model that aims to realize the human hand’s functionality using a single type of 3D-printable material. Our robotic hand 3D model is combined with bones, ligaments, tendons, pulley systems, and tissue. We also describe the fabrication method to rapidly produce our robotic hand in 3D printing, wherein all parts are made by elastic 50 A (shore durometer) resin. In the experimental section, we show that our robotic hand has a similar motion range to a human hand with substantial grasping strength and compare it with the latest other designs of anthropomorphic robotic hands. Our new design greatly reduces the fabrication cost and assembly time. Compared with other robotic hand designs, we think our robotic hand may induce a new approach to the design and production of robotic hands as well as other related mechanical structures.

scholarly journals Algorithm of Myoelectric Signals Processing for the Control of Prosthetic Robotic Hands

2018 ◽  
Vol 18 (01) ◽  
pp. e04 ◽  
Author(s):  
Rodrigo E. Russo ◽  
Juana G. Fernández ◽  
Raúl R. Rivera
Keyword(s):  
Nervous System ◽  
Peripheral Nervous System ◽  
Robotic Hand ◽  
Robotic Hands ◽  
Myoelectric Signals ◽  
Electrical Signals ◽  
Artificial Hand ◽  
And Control ◽  
The Relationship ◽  
The Brain

The development of robotic hand prosthetic aims to give back people with disabilities, the ability to recover the functionality needed to manipulate the objects of their daily environment. The electrical signals sent by the brain through the nervous system are associated with the type of movement that the limbs must execute. Myoelectric sensors are non-intrusive devices that allow the capture of electrical signals from the peripheral nervous system. The relationship between the signals originated in the brain tending to generate an action and the myoelectric ones as a result of them, are weakly correlated. For this reason, it is necessary to study their interaction in order to develop the algorithms that allow recognizing orders and transform them into commands that activate the corresponding movements of the prosthesis.The present work shows the development of a prosthesis based on the design of an artificial hand Open Bionics to produce the movements, the MyoWare Muscle sensor for the capture of myoelectric signals (EMG) and the algorithm that allows to identify orders associated with three types of movement. Arduino Nano module performs the acquisition and control processes to meet the size and consumption requirements of this application.

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