4,407 research outputs found
On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation
Biological and robotic grasp and manipulation are undeniably similar at the
level of mechanical task performance. However, their underlying fundamental
biological vs. engineering mechanisms are, by definition, dramatically
different and can even be antithetical. Even our approach to each is
diametrically opposite: inductive science for the study of biological systems
vs. engineering synthesis for the design and construction of robotic systems.
The past 20 years have seen several conceptual advances in both fields and the
quest to unify them. Chief among them is the reluctant recognition that their
underlying fundamental mechanisms may actually share limited common ground,
while exhibiting many fundamental differences. This recognition is particularly
liberating because it allows us to resolve and move beyond multiple paradoxes
and contradictions that arose from the initial reasonable assumption of a large
common ground. Here, we begin by introducing the perspective of neuromechanics,
which emphasizes that real-world behavior emerges from the intimate
interactions among the physical structure of the system, the mechanical
requirements of a task, the feasible neural control actions to produce it, and
the ability of the neuromuscular system to adapt through interactions with the
environment. This allows us to articulate a succinct overview of a few salient
conceptual paradoxes and contradictions regarding under-determined vs.
over-determined mechanics, under- vs. over-actuated control, prescribed vs.
emergent function, learning vs. implementation vs. adaptation, prescriptive vs.
descriptive synergies, and optimal vs. habitual performance. We conclude by
presenting open questions and suggesting directions for future research. We
hope this frank assessment of the state-of-the-art will encourage and guide
these communities to continue to interact and make progress in these important
areas
Autonomy Infused Teleoperation with Application to BCI Manipulation
Robot teleoperation systems face a common set of challenges including
latency, low-dimensional user commands, and asymmetric control inputs. User
control with Brain-Computer Interfaces (BCIs) exacerbates these problems
through especially noisy and erratic low-dimensional motion commands due to the
difficulty in decoding neural activity. We introduce a general framework to
address these challenges through a combination of computer vision, user intent
inference, and arbitration between the human input and autonomous control
schemes. Adjustable levels of assistance allow the system to balance the
operator's capabilities and feelings of comfort and control while compensating
for a task's difficulty. We present experimental results demonstrating
significant performance improvement using the shared-control assistance
framework on adapted rehabilitation benchmarks with two subjects implanted with
intracortical brain-computer interfaces controlling a seven degree-of-freedom
robotic manipulator as a prosthetic. Our results further indicate that shared
assistance mitigates perceived user difficulty and even enables successful
performance on previously infeasible tasks. We showcase the extensibility of
our architecture with applications to quality-of-life tasks such as opening a
door, pouring liquids from containers, and manipulation with novel objects in
densely cluttered environments
New developments in prosthetic arm systems
Absence of an upper limb leads to severe impairments in everyday life, which can further influence the social and mental state. For these reasons, early developments in cosmetic and body-driven prostheses date some centuries ago, and they have been evolving ever since. Following the end of the Second World War, rapid developments in technology resulted in powered myoelectric hand prosthetics. In the years to come, these devices were common on the market, though they still suffered high user abandonment rates. The reasons for rejection were trifold - insufficient functionality of the hardware, fragile design, and cumbersome control. In the last decade, both academia and industry have reached major improvements concerning technical features of upper limb prosthetics and methods for their interfacing and control. Advanced robotic hands are offered by several vendors and research groups, with a variety of active and passive wrist options that can be articulated across several degrees of freedom. Nowadays, elbow joint designs include active solutions with different weight and power options. Control features are getting progressively more sophisticated, offering options for multiple sensor integration and multi-joint articulation. Latest developments in socket designs are capable of facilitating implantable and multiple surface electromyography sensors in both traditional and osseointegration-based systems. Novel surgical techniques in combination with modern, sophisticated hardware are enabling restoration of dexterous upper limb functionality. This article is aimed at reviewing the latest state of the upper limb prosthetic market, offering insights on the accompanying technologies and techniques. We also examine the capabilities and features of some of academia’s flagship solutions and methods
A dynamic tactile sensor on photoelastic effect
Certain photoelastic materials exhibit birefringent characteristics at a very low level of strain. This property of material may be suitable for dynamic or wave propagation studies, which can be exploited for designing tactile sensors. This paper presents the design, construction and testing of a novel dynamic sensor based on photoelastic effect, which is capable of detecting object slip as well as providing normal force information. The paper investigates the mechanics of object slip, and develops an approximate model of the sensor. This allows visualization of various parameters involved in the sensor design. The model also explains design improvements necessary to obtain continuous signal during object slip. The developed sensor has been compared with other existing sensors and experimental results from the sensor have been discussed. The sensor is calibrated for normal force which is in addition to the dynamic signal that it provides from the same contact location. The sensor has a simple design and is of a small size allowing it to be incorporated into robotic fingers, and it provides output signals which are largely unaffected by external disturbances
The PRISMA Hand II: A Sensorized Robust Hand for Adaptive Grasp and In-Hand Manipulation
Although substantial progresses have been made in building anthropomorphic robotic hands, lack of mechanical robustness, dexterity and force sensation still restrains wide adoption of robotic prostheses. This paper presents the design and preliminary evaluation of the PRISMA hand II, which is a mechanically robust anthropomorphic hand developed at the PRISMA Lab of University of Naples Federico II. The hand is highly underactuated, as the 19 finger joints are driven by three motors via elastic tendons. Nevertheless, the hand can performs not only adaptive grasps but also in-hand manipulation. The hand uses rolling contact joints, which is compliant in multiple directions. Force sensor are integrated to each fingertip in order to provide force feedback during grasping and manipulation. Preliminary experiments have been performed to evaluate the hand. Results show that the hand can perform various grasps and in-hand manipulation, while the structure can withstand severe disarticulation. This suggests that the proposed design can be a viable solution for robust and dexterous prosthetic hands
Design of a robotic hand with a biologically-inspired parallel actuation system for prosthetic applications
Trabajo presentado al 34th Annual Mechanisms and Robotics Conference celebrado en Quebec del 15 al 18 de agosto de 2010.This paper presents the design of a robotic hand for prosthetic applications. The main characteristic of this robotic hand is its biologically-inspired parallel actuation system, which is based on the behavior/strength space of the Flexor Digitorum Profundus (FDP) and the Flexor Digitorum Superficialis (FDS) muscles. The design separates the strength space of the FDS and FDP muscles into a lighter strength region where finer manipulation and general approach tasks are executed, and a higher strength region where the more robust grasps are achieved. Two parallel actuator types and kinematic structures are designed to complement the requirements of both strength space regions.This research was performed under an award/contract from Telemedicine Advanced Technology Research Center (TATRC), of the U.S. Army Medical Research and Materiel Command
(USAMRMC) of the U.S. Department of Defense.Peer Reviewe
Sensors for Robotic Hands: A Survey of State of the Art
Recent decades have seen significant progress in the field of artificial hands. Most of the
surveys, which try to capture the latest developments in this field, focused on actuation and control systems of these devices. In this paper, our goal is to provide a comprehensive survey of the sensors for artificial hands. In order to present the evolution of the field, we cover five year periods starting at the turn of the millennium. At each period, we present the robot hands with a focus on their sensor systems dividing them into categories, such as prosthetics, research devices, and industrial end-effectors.We also cover the sensors developed for robot hand usage in each era. Finally, the period between 2010 and 2015 introduces the reader to the state of the art and also hints to the future directions in the sensor development for artificial hands
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