451 research outputs found
Fingertip Proximity Sensor with Realtime Visual-based Calibration
Proximity and distance estimation sensors are broadly used in robotic hands to enhance the quality of grasping during grasp planning, grasp correction and in-hand manipulation. This paper presents a fiber optical proximity sensor that is integrated with a tactile sensing fingertip of a robotic hand of a mobile robot. The distance estimation of proximity sensors are typically influenced by the reflective properties of an object, such as color or surface roughness. With the approach proposed in this paper, the accuracy of the proximity sensor is enhanced using the information collected by the vision system of the robot. A camera is employed to obtain RGB values of the object to be grasped. Further on, the data obtained from the camera is used to obtain the correct calibration for the proximity sensor. Based on the experimental evidence, it is shown that our approach can be effectively used to reduce the distance estimation error
Design of a Multimodal Fingertip Sensor for Dynamic Manipulation
We introduce a spherical fingertip sensor for dynamic manipulation. It is
based on barometric pressure and time-of-flight proximity sensors and is
low-latency, compact, and physically robust. The sensor uses a trained neural
network to estimate the contact location and three-axis contact forces based on
data from the pressure sensors, which are embedded within the sensor's sphere
of polyurethane rubber. The time-of-flight sensors face in three different
outward directions, and an integrated microcontroller samples each of the
individual sensors at up to 200 Hz. To quantify the effect of system latency on
dynamic manipulation performance, we develop and analyze a metric called the
collision impulse ratio and characterize the end-to-end latency of our new
sensor. We also present experimental demonstrations with the sensor, including
measuring contact transitions, performing coarse mapping, maintaining a contact
force with a moving object, and reacting to avoid collisions.Comment: 6 pages, 2 pages of references, supplementary video at
https://youtu.be/HGSdcW_aans. Submitted to ICRA 202
Improved GelSight Tactile Sensor for Measuring Geometry and Slip
A GelSight sensor uses an elastomeric slab covered with a reflective membrane
to measure tactile signals. It measures the 3D geometry and contact force
information with high spacial resolution, and successfully helped many
challenging robot tasks. A previous sensor, based on a semi-specular membrane,
produces high resolution but with limited geometry accuracy. In this paper, we
describe a new design of GelSight for robot gripper, using a Lambertian
membrane and new illumination system, which gives greatly improved geometric
accuracy while retaining the compact size. We demonstrate its use in measuring
surface normals and reconstructing height maps using photometric stereo. We
also use it for the task of slip detection, using a combination of information
about relative motions on the membrane surface and the shear distortions. Using
a robotic arm and a set of 37 everyday objects with varied properties, we find
that the sensor can detect translational and rotational slip in general cases,
and can be used to improve the stability of the grasp.Comment: IEEE/RSJ International Conference on Intelligent Robots and System
Fingertip Fiber Optical Tactile Array with Two-Level Spring Structure
Tactile perception is a feature benefiting reliable grasping and manipulation. This paper presents the design of an integrated fingertip force sensor employing an optical fiber based approach where applied forces modulate light intensity. The proposed sensor system is developed to support grasping of a broad range of objects, including those that are hard as well those that are soft. The sensor system is comprised of four sensing elements forming a tactile array integrated with the tip of a finger. We investigate the design configuration of a separate force sensing element with the aim to improve its measurement range. The force measurement of a single tactile element is based on a two-level displacement that is achieved thanks to a hybrid sensing structure made up of a stiff linear and flexible ortho-planar spring. An important outcome of this paper is a miniature tactile fingertip sensor that is capable of perceiving light contact, typically occurring during the initial stages of a grasp, as well as measuring higher forces, commonly present during tight grasps
A Fingertip Sensor and Algorithms for Pre-touch Distance Ranging and Material Detection in Robotic Grasping
To enhance robotic grasping capabilities, we are developing new contactless
fingertip sensors to measure distance in close proximity and simultaneously
detect the type of material and the interior structure. These sensors are
referred to as pre-touch dual-modal and dual-mechanism (PDM) sensors, and
they operate using both pulse-echo ultrasound (US) and optoacoustic (OA)
modalities. We present the design of a PDM sensor that utilizes a pulsed
laser beam and a customized ultrasound transceiver with a wide acoustic
bandwidth for ranging and sensing. Both US and OA signals are collected
simultaneously, triggered by the same laser pulse. To validate our design, we
have fabricated a prototype of the PDM sensor and integrated it into an
object scanning system. We have also developed algorithms to enable the sensor,
including time-of-flight (ToF) auto estimation, ranging rectification, sensor
and system calibration, distance ranging, material/structure detection, and
object contour detection and reconstruction. The experimental results
demonstrate that the new PDM sensor and its algorithms effectively enable
the object scanning system to achieve satisfactory ranging and contour
reconstruction performances, along with satisfying material/structure detection
capabilities. In conclusion, the PDM sensor offers a practical and powerful
solution to improve grasping of unknown objects with the robotic gripper by
providing advanced perception capabilities
Fibre Optic-Based Force Sensor for Bio-Mimetic Robotic Finger
A novel optical-based fingertip force sensor, which
is integrated in a bio-mimetic finger for robotic and prosthetic manipulation is presented. This is used to obtain tactile information during grasping and manipulation of objects.
Unlike most devices the proposed force sensor is free of
any electrical and metal components and as such is immune to electromagnetic fields. The sensor is simple and very compact, has extremely low power consumption and noise levels and requires no additional hardware. It is based on a cantilever design combined with fiber optics and is integrated on the distal phalange of a robotic finger.
The unique design of this sensor makes it ideally suited
for use in messy or harsh environments that may be prone to electromagnetic fields, granular or liquid intrusion, may include combustible gasses or be subject to radiatio
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
An Embedded, Multi-Modal Sensor System for Scalable Robotic and Prosthetic Hand Fingers
Grasping and manipulation with anthropomorphic robotic and prosthetic hands presents a scientific challenge regarding mechanical design, sensor system, and control. Apart from the mechanical design of such hands, embedding sensors needed for closed-loop control of grasping tasks remains a hard problem due to limited space and required high level of integration of different components. In this paper we present a scalable design model of artificial fingers, which combines mechanical design and embedded electronics with a sophisticated multi-modal sensor system consisting of sensors for sensing normal and shear force, distance, acceleration, temperature, and joint angles. The design is fully parametric, allowing automated scaling of the fingers to arbitrary dimensions in the human hand spectrum. To this end, the electronic parts are composed of interchangeable modules that facilitate the echanical scaling of the fingers and are fully enclosed by the mechanical parts of the finger. The resulting design model allows deriving freely scalable and multimodally sensorised fingers for robotic and prosthetic hands. Four physical demonstrators are assembled and tested to evaluate the approach
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