Visual-Servoing Control of Robot Hand with Estimation of Full Articulation of Human Hand

2014 ◽  
Vol 625 ◽  
pp. 728-735
Author(s):  
Motomasa Tomida ◽  
Kiyoshi Hoshino

A depth sensor or depth camera is available at a reasonable cost in recent years. Due to the excessive dispersion of depth values outputted from the depth camera, however, changes in the pose cannot be directly employed for complicated hand pose estimation. The authors therefore propose a visual-servoing controlled robotic hand with RGB high-speed cameras. Two cameras have their own database in the system. Each data set has proportional information of each hand image and image features for matching, and joint angle data for output as estimated results. Once sequential hand images are recorded with two high-speed RGB cameras, the system first selects one database with bigger size of hand region in each recorded image. Second, a coarse screening is carried out according to the proportional information on the hand image which roughly corresponds to wrist rotation, or thumb or finger extension. Third, a detailed search is performed for similarity among the selected candidates. The estimated results are transmitted to a robot hand so that the same motions of an operator is reconstructed in the robot without time delay.

Author(s):  
Thomas E. Pillsbury ◽  
Ryan M. Robinson ◽  
Norman M. Wereley

Pneumatic artificial muscles (PAMs) are used in robotics applications for their light-weight design and superior static performance. Additional PAM benefits are high specific work, high force density, simple design, and long fatigue life. Previous use of PAMs in robotics research has focused on using “large,” full-scale PAMs as actuators. Large PAMs work well for applications with large working volumes that require high force and torque outputs, such as robotic arms. However, in the case of a compact robotic hand, a large number of degrees of freedom are required. A human hand has 35 muscles, so for similar functionality, a robot hand needs a similar number of actuators that must fit in a small volume. Therefore, using full scale PAMs to actuate a robot hand requires a large volume which for robotics and prosthetics applications is not feasible, and smaller actuators, such as miniature PAMs, must be used. In order to develop a miniature PAM capable of producing the forces and contractions needed in a robotic hand, different braid and bladder material combinations were characterized to determine the load stroke profiles. Through this characterization, miniature PAMs were shown to have comparably high force density with the benefit of reduced actuator volume when compared to full scale PAMs. Testing also showed that braid-bladder interactions have an important effect at this scale, which cannot be modeled sufficiently using existing methods without resorting to a higher-order constitutive relationship. Due to the model inaccuracies and the limited selection of commercially available materials at this scale, custom molded bladders were created. PAMs created with these thin, soft bladders exhibited greatly improved performance.


1993 ◽  
Vol 2 (3) ◽  
pp. 203-220 ◽  
Author(s):  
Robert N. Rohling ◽  
John M. Hollerbach ◽  
Stephen C. Jacobsen

An optimized fingertip mapping (OFM) algorithm has been developed to transform human hand poses into robot hand poses. It has been implemented to teleoperate the Utah/MIT Dextrous Hand by a new hand master: the Utah Dextrous Hand Master. The keystone of the algorithm is the mapping of both the human fingertip positions and orientations to the robot fingers. Robot hand poses are generated by minimizing the errors between desired human fingertip positions and orientations and possible robot fingertip positions and orientations. Differences in the fingertip workspaces that arise from kinematic dissimilarities between the human and robot hands are accounted for by the use of a priority based mapping strategy. The OFM gives first priority to the human fingertip position goals and the second to orientation.


2011 ◽  
Vol 23 (3) ◽  
pp. 345-352 ◽  
Author(s):  
Jun-Ya Nagase ◽  
Norihiko Saga ◽  
Toshiyuki Satoh ◽  
Koichi Suzumori

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.


2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Wataru Fukui ◽  
Futoshi Kobayashi ◽  
Fumio Kojima ◽  
Hiroyuki Nakamoto ◽  
Nobuaki Imamura ◽  
...  

We have developed a universal robot hand with tactile and other sensors. An array-type tactile sensor is crucial for dexterous manipulation of objects using a robotic hand, since this sensor can measure the pressure distribution on finger pads. The sensor has a very high resolution, and the shape of a grasped object can be classified by using this sensor. The more the number of measurement points provided, the higher the accuracy of the classification, but with a corresponding lengthening of the measurement cycle. In this paper, the problem of slow response time is resolved by using software for an array-type tactile sensor with high resolution that emulates the human sensor system. The validity of the proposed method is demonstrated through experiments.


Author(s):  
Mohamad Aizat Abdul Wahit ◽  
Fatimahtul Zahrah Romzi ◽  
Siti Anom Ahmad ◽  
Mohd Hamiruce Marhaban ◽  
Wada Chikamune

Developing an anthropomorphic robotic hand (ARH) has become a relevant research field due to the need to help the amputees live their life as normal people. However, the current state of research is unsatisfactory, especially in terms of structural design and the robot control method. This paper, which proposes a 3D printed ARH structure that follows the average size of an adult human hand, consists of five fingers with a tendon-driven actuator mechanism embedded in each finger structure. Besides that, the movement capability of the developed 3D printed robot hand validated by using motion capture analysis to ensure the similarity to the expected motion range in structural design is achieved. Its system functionality test was conducted in three stages: (1) muscular activity detection, (2) object detection for individual finger movement control, and (3) integration of both stages in one algorithm. Finally, an ARH was developed, which resembles human hand features, as well as a reliable system that can perform opened hand palm and some grasping postures for daily use.


Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 41
Author(s):  
Yuji Yamakawa ◽  
Yugo Katsuki ◽  
Yoshihiro Watanabe ◽  
Masatoshi Ishikawa

This paper focuses on development of a high-speed, low-latency telemanipulated robot hand system, evaluation of the system, and demonstration of the system. The characteristics of the developed system are the followings: non-contact, high-speed 3D visual sensing of the human hand, intuitive motion mapping between human hands and robot hands, and low-latency, fast responsiveness to human hand motion. Such a high-speed, low-latency telemanipulated robot hand system can be considered to be more effective from the viewpoint of usability. The developed system consists of a high-speed vision system, a high-speed robot hand, and a real-time controller. For the developed system, we propose new methods of 3D sensing, mapping between the human hand and the robot hand, and the robot hand control. We evaluated the performance (latency and responsiveness) of the developed system. As a result, the latency of the developed system is so small that humans cannot recognize the latency. In addition, we conducted experiments of opening/closing motion, object grasping, and moving object grasping as demonstrations. Finally, we confirmed the validity and effectiveness of the developed system and proposed method.


Author(s):  
Miao Yu ◽  
Jinxing Shen ◽  
Changxi Ma

Because of the high percentage of fatalities and severe injuries in wrong-way driving (WWD) crashes, numerous studies have focused on identifying contributing factors to the occurrence of WWD crashes. However, a limited number of research effort has investigated the factors associated with driver injury-severity in WWD crashes. This study intends to bridge the gap using a random parameter logit model with heterogeneity in means and variances approach that can account for the unobserved heterogeneity in the data set. Police-reported crash data collected from 2014 to 2017 in North Carolina are used. Four injury-severity levels are defined: fatal injury, severe injury, possible injury, and no injury. Explanatory variables, including driver characteristics, roadway characteristics, environmental characteristics, and crash characteristics, are used. Estimation results demonstrate that factors, including the involvement of alcohol, rural area, principal arterial, high speed limit (>60 mph), dark-lighted conditions, run-off-road collision, and head-on collision, significantly increase the severity levels in WWD crashes. Several policy implications are designed and recommended based on findings.


2017 ◽  
Vol 37 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Haluk Ay ◽  
Anthony Luscher ◽  
Carolyn Sommerich

Purpose The purpose of this study is to design and develop a testing device to simulate interaction between human hand–arm dynamics, right-angle (RA) computer-controlled power torque tools and joint-tightening task-related variables. Design/methodology/approach The testing rig can simulate a variety of tools, tasks and operator conditions. The device includes custom data-acquisition electronics and graphical user interface-based software. The simulation of the human hand–arm dynamics is based on the rig’s four-bar mechanism-based design and mechanical components that provide adjustable stiffness (via pneumatic cylinder) and mass (via plates) and non-adjustable damping. The stiffness and mass values used are based on an experimentally validated hand–arm model that includes a database of model parameters. This database is with respect to gender and working posture, corresponding to experienced tool operators from a prior study. Findings The rig measures tool handle force and displacement responses simultaneously. Peak force and displacement coefficients of determination (R2) between rig estimations and human testing measurements were 0.98 and 0.85, respectively, for the same set of tools, tasks and operator conditions. The rig also provides predicted tool operator acceptability ratings, using a data set from a prior study of discomfort in experienced operators during torque tool use. Research limitations/implications Deviations from linearity may influence handle force and displacement measurements. Stiction (Coulomb friction) in the overall rig, as well as in the air cylinder piston, is neglected. The rig’s mechanical damping is not adjustable, despite the fact that human hand–arm damping varies with respect to gender and working posture. Deviations from these assumptions may affect the correlation of the handle force and displacement measurements with those of human testing for the same tool, task and operator conditions. Practical implications This test rig will allow the rapid assessment of the ergonomic performance of DC torque tools, saving considerable time in lineside applications and reducing the risk of worker injury. DC torque tools are an extremely effective way of increasing production rate and improving torque accuracy. Being a complex dynamic system, however, the performance of DC torque tools varies in each application. Changes in worker mass, damping and stiffness, as well as joint stiffness and tool program, make each application unique. This test rig models all of these factors and allows quick assessment. Social implications The use of this tool test rig will help to identify and understand risk factors that contribute to musculoskeletal disorders (MSDs) associated with the use of torque tools. Tool operators are subjected to large impulsive handle reaction forces, as joint torque builds up while tightening a fastener. Repeated exposure to such forces is associated with muscle soreness, fatigue and physical stress which are also risk factors for upper extremity injuries (MSDs; e.g. tendinosis, myofascial pain). Eccentric exercise exertions are known to cause damage to muscle tissue in untrained individuals and affect subsequent performance. Originality/value The rig provides a novel means for quantitative, repeatable dynamic evaluation of RA powered torque tools and objective selection of tightening programs. Compared to current static tool assessment methods, dynamic testing provides a more realistic tool assessment relative to the tool operator’s experience. This may lead to improvements in tool or controller design and reduction in associated musculoskeletal discomfort in operators.


2020 ◽  
Vol 53 (2) ◽  
pp. 9796-9801
Author(s):  
Ryosuke Higo ◽  
Taku Senoo ◽  
Masatoshi Ishikawa
Keyword(s):  

2020 ◽  
Vol 12 ◽  
pp. 175682932092452
Author(s):  
Liang Lu ◽  
Alexander Yunda ◽  
Adrian Carrio ◽  
Pascual Campoy

This paper presents a novel collision-free navigation system for the unmanned aerial vehicle based on point clouds that outperform compared to baseline methods, enabling high-speed flights in cluttered environments, such as forests or many indoor industrial plants. The algorithm takes the point cloud information from physical sensors (e.g. lidar, depth camera) and then converts it to an occupied map using Voxblox, which is then used by a rapid-exploring random tree to generate finite path candidates. A modified Covariant Hamiltonian Optimization for Motion Planning objective function is used to select the best candidate and update it. Finally, the best candidate trajectory is generated and sent to a Model Predictive Control controller. The proposed navigation strategy is evaluated in four different simulation environments; the results show that the proposed method has a better success rate and a shorter goal-reaching distance than the baseline method.


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