Design method for an anthropomorphic hand able to gesture and grasp

This paper presents a numerical method to conceive and design the kinematic model of an anthropomorphic robotic hand used for gesturing and grasping. In literature, there are few numerical methods for the finger placement of human-inspired robotic hands. In particular, there are no numerical methods, for the thumb placement, that aim to improve the hand dexterity and grasping capabilities by keeping the hand design close to the human one. While existing models are usually the result of successive parameter adjustments, the proposed method determines the fingers placements by mean of empirical tests. Moreover, a surgery test and the workspace analysis of the whole hand are used to find the best thumb position and orientation according to the hand kinematics and structure. The result is validated through simulation where it is checked that the hand looks well balanced and that it meets our constraints and needs. The presented method provides a numerical tool which allows the easy computation of finger and thumb geometries and base placements for a human-like dexterous robotic hand.Comment: IEEE International Conference on Robotics and Automation, May 2015, Seattle, United States. IEEE, 2015, Proceeding IEEE International Conference on Robotics and Automatio

Intersegmental Coordination in the Kinematics of Prehension Movements of Macaques

The most popular model to explain how prehensile movements are organized assumes that they comprise two "components", the reaching component encoding information regarding the object's spatial location and the grasping component encoding information on the object's intrinsic properties such as size and shape. Comparative kinematic studies on grasping behavior in the humans and in macaques have been carried out to investigate the similarities and differences existing across the two species. Although these studies seem to favor the hypothesis that macaques and humans share a number of kinematic features it remains unclear how the reaching and grasping components are coordinated during prehension movements in free-ranging macaque monkeys. Twelve hours of video footage was filmed of the monkeys as they snatched food items from one another (i.e., snatching) or collect them in the absence of competitors (i.e., unconstrained). The video samples were analyzed frame-by-frame using digitization techniques developed to perform two-dimensional post-hoc kinematic analyses of the two types of actions. The results indicate that only for the snatching condition when the reaching variability increased there was an increase in the amplitude of maximum grip aperture. Besides, the start of a break-point along the deceleration phase of the velocity profile correlated with the time at which maximum grip aperture occurred. These findings suggest that macaques can spatially and temporally couple the reaching and the grasping components when there is pressure to act quickly. They offer a substantial contribution to the debate about the nature of how prehensile actions are programmed

Synergy-based Hand Pose Sensing: Reconstruction Enhancement

Low-cost sensing gloves for reconstruction posture provide measurements which are limited under several regards. They are generated through an imperfectly known model, are subject to noise, and may be less than the number of Degrees of Freedom (DoFs) of the hand. Under these conditions, direct reconstruction of the hand posture is an ill-posed problem, and performance can be very poor. This paper examines the problem of estimating the posture of a human hand using(low-cost) sensing gloves, and how to improve their performance by exploiting the knowledge on how humans most frequently use their hands. To increase the accuracy of pose reconstruction without modifying the glove hardware - hence basically at no extra cost - we propose to collect, organize, and exploit information on the probabilistic distribution of human hand poses in common tasks. We discuss how a database of such an a priori information can be built, represented in a hierarchy of correlation patterns or postural synergies, and fused with glove data in a consistent way, so as to provide a good hand pose reconstruction in spite of insufficient and inaccurate sensing data. Simulations and experiments on a low-cost glove are reported which demonstrate the effectiveness of the proposed techniques.Comment: Submitted to International Journal of Robotics Research (2012

What Will I Do Next? The Intention from Motion Experiment

In computer vision, video-based approaches have been widely explored for the early classification and the prediction of actions or activities. However, it remains unclear whether this modality (as compared to 3D kinematics) can still be reliable for the prediction of human intentions, defined as the overarching goal embedded in an action sequence. Since the same action can be performed with different intentions, this problem is more challenging but yet affordable as proved by quantitative cognitive studies which exploit the 3D kinematics acquired through motion capture systems. In this paper, we bridge cognitive and computer vision studies, by demonstrating the effectiveness of video-based approaches for the prediction of human intentions. Precisely, we propose Intention from Motion, a new paradigm where, without using any contextual information, we consider instantaneous grasping motor acts involving a bottle in order to forecast why the bottle itself has been reached (to pass it or to place in a box, or to pour or to drink the liquid inside). We process only the grasping onsets casting intention prediction as a classification framework. Leveraging on our multimodal acquisition (3D motion capture data and 2D optical videos), we compare the most commonly used 3D descriptors from cognitive studies with state-of-the-art video-based techniques. Since the two analyses achieve an equivalent performance, we demonstrate that computer vision tools are effective in capturing the kinematics and facing the cognitive problem of human intention prediction.Comment: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshop

Perkaitan di antara status sosioekonomi keluarga dengan Pencapaian akademik pelajar aliran teknikal

Selain daripada mengendalikan fungsi pendidikan, sekolah juga diberikan peranan bagi menyediakan tenaga mahir untuk memenuhi keperluan ekonomi negara. Sekolah aliran teknikal dilihat sebagai satu institusi khusus yang memainkan peranan tersebut. Namun begitu, terdapat pelbagai faktor yang boleh mempengaruhi pencapaian pelajar aliran teknikal ini. Tahap sosioekonomi keluarga telah dikenalpasti antara faktor yang boleh mempengaruhi pencapaian pelajar. Kajian ini dilakukan untuk mendapatkan perkaitan di antara tahap sosioekonomi keluarga seperti tahap pendidikan bapa, jumlah pendapatan dan saiz keluarga terhadap pencapaian akademik pelajar. Sampel kajian ini ialah pelajar-pelajar tingkatan 4 dan 5 yang menetap di asrama Sekolah Menengah Teknik Kuala Terengganu. Pelajar ini dipilih kerana mereka mendapat kemudahan dan persekitaran pembelajaran yang sama. Seramai 80 orang pelajar dalam jurusan teknikal dipilih secara rawak mudah. Keputusan kajian mendapati bahawa hanya saiz keluarga mempunyai korelasi yang tinggi berbanding tahap pencapaian akademik bapa dan jumlah pendapatan keluarga. Ini menunjukkan bahawa faktor saiz keluarga memberikan impak secara langsung kepada pencapaian pelajar walaupun mereka menetap di asrama yang menyediakan suasana dan kemudahan yang sama

Complementary Actions

Human beings come into the world wired for social interaction. At the fourteenth week of gestation, twin fetuses already display interactive movements specifically directed towards their co- twin. Readiness for social interaction is also clearly expressed by the newborn who imitate facial gestures, suggesting that there is a common representation mediating action observation and execution. While actions that are observed and those that are planned seem to be functionally equivalent, it is unclear if the visual representation of an observed action inevitably leads to its motor representation. This is particularly true with regard to complementary actions (from the Latin complementum ; i.e. that fills up), a specific class of movements which differ, while interacting, with observed ones. In geometry, angles are defined as complementary if they form a right angle. In art and design, complementary colors are color pairs that, when combined in the right proportions, produce white or black. As a working definition, complementary actions refer here to any form of social interaction wherein two (or more) individuals complete each other\u2019s actions in a balanced way. Successful complementary interactions are founded on the abilities:\ua0 (1)\ua0 to simulate another person\u2019s movements; (2)\ua0 to predict another person\u2019s future action/ s; (3)\ua0to produce an appropriate congruent/ incongruent response that completes the other person\u2019s action/ s; and (4)\ua0to integrate the predicted effects of one\u2019s own and another person\u2019s actions. It is the neurophysiological mechanism that underlies this process which forms the main theme of this chapte

Evolution of Prehension Ability in an Anthropomorphic Neurorobotic Arm

In this paper we show how a simulated anthropomorphic robotic arm controlled by an artificial neural network can develop effective reaching and grasping behaviour through a trial and error process in which the free parameters encode the control rules which regulate the fine-grained interaction between the robot and the environment and variations of the free parameters are retained or discarded on the basis of their effects at the level of the global behaviour exhibited by the robot situated in the environment. The obtained results demonstrate how the proposed methodology allows the robot to produce effective behaviours thanks to its ability to exploit the morphological properties of the robot’s body (i.e. its anthropomorphic shape, the elastic properties of its muscle-like actuators, and the compliance of its actuated joints) and the properties which arise from the physical interaction between the robot and the environment mediated by appropriate control rules

Hubungan di antara pengaturan kerja fleksibel dan prestasi pekerja dalam kalangan ejen insurans wanita

Ejen insurans merupakan jurujual pertengahan bagi syarikat insurans di mana mereka memainkan peranan penting dalam memberi khidmat nasihat kewangan (Hannah, 2011). Ejen insurans bekerja berdasarkan persekitaran pengaturan kerja yang fleksibel di mana mereka boleh menyediakan jadual waktu bekerja sendiri. Sebahagian daripada mereka bertemu dengan pelanggan pada waktu perniagaan siang hari, sementara yang lain pula membuat kertas kerja dan menyediakan konsultasi untuk pelanggan pada waktu petang. Kebanyakan mereka bekerja selama 40 jam seminggu dan ada juga beberapa ejen yang bekerja lebih lama daripada 40 jam (Hannah, 2011). Prestasi ejen insurans sangat penting untuk mengekalkan jenama produk insurans. Penilaian terhadap prestasi di kalangan ejen insurans biasanya bergantung kepada kejayaan atau kegagalan mencapai sasaran penjualan (Insurance Agent Job Overview, 2019). Proses menjual produk insurans memerlukan masa kerana mereka perlu mendekati pelanggan sebanyak mungkin dan ketersediaan waktu bekerja yang tidak tetap