537 research outputs found
Tactile Sensing for Robotic Applications
This chapter provides an overview of tactile sensing in robotics. This chapter is an attempt
to answer three basic questions:
\u2022 What is meant by Tactile Sensing?
\u2022 Why Tactile Sensing is important?
\u2022 How Tactile Sensing is achieved?
The chapter is organized to sequentially provide the answers to above basic questions.
Tactile sensing has often been considered as force sensing, which is not wholly true. In order
to clarify such misconceptions about tactile sensing, it is defined in section 2. Why tactile
section is important for robotics and what parameters are needed to be measured by tactile
sensors to successfully perform various tasks, are discussed in section 3. An overview of
`How tactile sensing has been achieved\u2019 is given in section 4, where a number of
technologies and transduction methods, that have been used to improve the tactile sensing
capability of robotic devices, are discussed. Lack of any tactile analog to Complementary
Metal Oxide Semiconductor (CMOS) or Charge Coupled Devices (CCD) optical arrays has
often been cited as one of the reasons for the slow development of tactile sensing vis-\ue0-vis
other sense modalities like vision sensing. Our own contribution \u2013 development of tactile
sensing arrays using piezoelectric polymers and involving silicon micromachining - is an
attempt in the direction of achieving tactile analog of CMOS optical arrays. The first phase
implementation of these tactile sensing arrays is discussed in section 5. Section 6 concludes
the chapter with a brief discussion on the present status of tactile sensing and the challenges
that remain to be solved
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Haptic Perception with a Robot Hand: Requirements and Realization
This paper first discusses briefly some of the recent ideas of perceptual psychology on the human haptic system particularly those of J.J. Gibson and Klatzky and Lederman. Following this introduction, we present some of the requirements of robotic haptic sensing and the results of experiments using a Utah/MIT dexterous robot hand to derive geometric object information using active sensing
Exoskeleton-covered soft finger with vision-based proprioception and tactile sensing
Soft robots offer significant advantages in adaptability, safety, and
dexterity compared to conventional rigid-body robots. However, it is
challenging to equip soft robots with accurate proprioception and tactile
sensing due to their high flexibility and elasticity. In this work, we describe
the development of a vision-based proprioceptive and tactile sensor for soft
robots called GelFlex, which is inspired by previous GelSight sensing
techniques. More specifically, we develop a novel exoskeleton-covered soft
finger with embedded cameras and deep learning methods that enable
high-resolution proprioceptive sensing and rich tactile sensing. To do so, we
design features along the axial direction of the finger, which enable
high-resolution proprioceptive sensing, and incorporate a reflective ink
coating on the surface of the finger to enable rich tactile sensing. We design
a highly underactuated exoskeleton with a tendon-driven mechanism to actuate
the finger. Finally, we assemble 2 of the fingers together to form a robotic
gripper and successfully perform a bar stock classification task, which
requires both shape and tactile information. We train neural networks for
proprioception and shape (box versus cylinder) classification using data from
the embedded sensors. The proprioception CNN had over 99\% accuracy on our
testing set (all six joint angles were within 1 degree of error) and had an
average accumulative distance error of 0.77 mm during live testing, which is
better than human finger proprioception. These proposed techniques offer soft
robots the high-level ability to simultaneously perceive their proprioceptive
state and peripheral environment, providing potential solutions for soft robots
to solve everyday manipulation tasks. We believe the methods developed in this
work can be widely applied to different designs and applications.Comment: Accepted to ICRA202
GelSight Baby Fin Ray: A Compact, Compliant, Flexible Finger with High-Resolution Tactile Sensing
The synthesis of tactile sensing with compliance is essential to many fields,
from agricultural usages like fruit picking, to sustainability practices such
as sorting recycling, to the creation of safe home-care robots for the elderly
to age with dignity. From tactile sensing, we can discern material properties,
recognize textures, and determine softness, while with compliance, we are able
to securely and safely interact with the objects and the environment around us.
These two abilities can culminate into a useful soft robotic gripper, such as
the original GelSight Fin Ray, which is able to grasp a large variety of
different objects and also perform a simple household manipulation task: wine
glass reorientation. Although the original GelSight Fin Ray solves the problem
of interfacing a generally rigid, high-resolution sensor with a soft, compliant
structure, we can improve the robustness of the sensor and implement techniques
that make such camera-based tactile sensors applicable to a wider variety of
soft robot designs. We first integrate flexible mirrors and incorporate the
rigid electronic components into the base of the gripper, which greatly
improves the compliance of the Fin Ray structure. Then, we synthesize a
flexible and high-elongation silicone adhesive-based fluorescent paint, which
can provide good quality 2D tactile localization results for our sensor.
Finally, we incorporate all of these techniques into a new design: the Baby Fin
Ray, which we use to dig through clutter, and perform successful classification
of nuts in their shells. The supplementary video can be found here:
https://youtu.be/_oD_QFtYTPMComment: Accepted to IEEE Conference of Soft Robotics (RoboSoft) 202
A fabric-based approach for wearable haptics
In recent years, wearable haptic systems (WHS) have gained increasing attention as a novel and exciting paradigm for human-robot interaction (HRI).These systems can be worn by users, carried around, and integrated in their everyday lives, thus enabling a more natural manner to deliver tactile cues.At the same time, the design of these types of devices presents new issues: the challenge is the correct identification of design guidelines, with the two-fold goal of minimizing system encumbrance and increasing the effectiveness and naturalness of stimulus delivery.Fabrics can represent a viable solution to tackle these issues.They are specifically thought “to be worn”, and could be the key ingredient to develop wearable haptic interfaces conceived for a more natural HRI.In this paper, the author will review some examples of fabric-based WHS that can be applied to different body locations, and elicit different haptic perceptions for different application fields.Perspective and future developments of this approach will be discussed
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