718 research outputs found
Active haptic perception in robots: a review
In the past few years a new scenario for robot-based applications has emerged. Service
and mobile robots have opened new market niches. Also, new frameworks for shop-floor
robot applications have been developed. In all these contexts, robots are requested to
perform tasks within open-ended conditions, possibly dynamically varying. These new
requirements ask also for a change of paradigm in the design of robots: on-line and safe
feedback motion control becomes the core of modern robot systems. Future robots will
learn autonomously, interact safely and possess qualities like self-maintenance. Attaining
these features would have been relatively easy if a complete model of the environment
was available, and if the robot actuators could execute motion commands perfectly
relative to this model. Unfortunately, a complete world model is not available and robots
have to plan and execute the tasks in the presence of environmental uncertainties which
makes sensing an important component of new generation robots. For this reason,
today\u2019s new generation robots are equipped with more and more sensing components,
and consequently they are ready to actively deal with the high complexity of the real
world. Complex sensorimotor tasks such as exploration require coordination between the
motor system and the sensory feedback. For robot control purposes, sensory feedback
should be adequately organized in terms of relevant features and the associated data
representation. In this paper, we propose an overall functional picture linking sensing
to action in closed-loop sensorimotor control of robots for touch (hands, fingers). Basic
qualities of haptic perception in humans inspire the models and categories comprising the
proposed classification. The objective is to provide a reasoned, principled perspective on
the connections between different taxonomies used in the Robotics and human haptic
literature. The specific case of active exploration is chosen to ground interesting use
cases. Two reasons motivate this choice. First, in the literature on haptics, exploration has
been treated only to a limited extent compared to grasping and manipulation. Second,
exploration involves specific robot behaviors that exploit distributed and heterogeneous
sensory data
A continuum robotic platform for endoscopic non-contact laser surgery: design, control, and preclinical evaluation
The application of laser technologies in surgical interventions has been accepted in the clinical
domain due to their atraumatic properties. In addition to manual application of fibre-guided
lasers with tissue contact, non-contact transoral laser microsurgery (TLM) of laryngeal tumours
has been prevailed in ENT surgery. However, TLM requires many years of surgical training
for tumour resection in order to preserve the function of adjacent organs and thus preserve the
patientâs quality of life. The positioning of the microscopic laser applicator outside the patient
can also impede a direct line-of-sight to the target area due to anatomical variability and limit
the working space. Further clinical challenges include positioning the laser focus on the tissue
surface, imaging, planning and performing laser ablation, and motion of the target area during
surgery. This dissertation aims to address the limitations of TLM through robotic approaches and
intraoperative assistance. Although a trend towards minimally invasive surgery is apparent, no
highly integrated platform for endoscopic delivery of focused laser radiation is available to date.
Likewise, there are no known devices that incorporate scene information from endoscopic imaging
into ablation planning and execution. For focusing of the laser beam close to the target tissue, this
work first presents miniaturised focusing optics that can be integrated into endoscopic systems.
Experimental trials characterise the optical properties and the ablation performance. A robotic
platform is realised for manipulation of the focusing optics. This is based on a variable-length
continuum manipulator. The latter enables movements of the endoscopic end effector in five
degrees of freedom with a mechatronic actuation unit. The kinematic modelling and control of the
robot are integrated into a modular framework that is evaluated experimentally. The manipulation
of focused laser radiation also requires precise adjustment of the focal position on the tissue. For
this purpose, visual, haptic and visual-haptic assistance functions are presented. These support
the operator during teleoperation to set an optimal working distance. Advantages of visual-haptic
assistance are demonstrated in a user study. The system performance and usability of the overall
robotic system are assessed in an additional user study. Analogous to a clinical scenario, the
subjects follow predefined target patterns with a laser spot. The mean positioning accuracy of the
spot is 0.5 mm. Finally, methods of image-guided robot control are introduced to automate laser
ablation. Experiments confirm a positive effect of proposed automation concepts on non-contact
laser surgery.Die Anwendung von Lasertechnologien in chirurgischen Interventionen hat sich aufgrund der atraumatischen Eigenschaften in der Klinik etabliert. Neben manueller Applikation von fasergefĂŒhrten
Lasern mit Gewebekontakt hat sich die kontaktfreie transorale Lasermikrochirurgie (TLM) von
Tumoren des Larynx in der HNO-Chirurgie durchgesetzt. Die TLM erfordert zur Tumorresektion
jedoch ein langjÀhriges chirurgisches Training, um die Funktion der angrenzenden Organe zu
sichern und damit die LebensqualitĂ€t der Patienten zu erhalten. Die Positionierung des mikroskopis chen Laserapplikators auĂerhalb des Patienten kann zudem die direkte Sicht auf das Zielgebiet
durch anatomische VariabilitÀt erschweren und den Arbeitsraum einschrÀnken. Weitere klinische
Herausforderungen betreffen die Positionierung des Laserfokus auf der GewebeoberflÀche, die
Bildgebung, die Planung und AusfĂŒhrung der Laserablation sowie intraoperative Bewegungen
des Zielgebietes. Die vorliegende Dissertation zielt darauf ab, die Limitierungen der TLM durch
robotische AnsÀtze und intraoperative Assistenz zu adressieren. Obwohl ein Trend zur minimal
invasiven Chirurgie besteht, sind bislang keine hochintegrierten Plattformen fĂŒr die endoskopische
Applikation fokussierter Laserstrahlung verfĂŒgbar. Ebenfalls sind keine Systeme bekannt, die
Szeneninformationen aus der endoskopischen Bildgebung in die Ablationsplanung und -ausfĂŒhrung
einbeziehen. FĂŒr eine situsnahe Fokussierung des Laserstrahls wird in dieser Arbeit zunĂ€chst
eine miniaturisierte Fokussieroptik zur Integration in endoskopische Systeme vorgestellt. Experimentelle Versuche charakterisieren die optischen Eigenschaften und das Ablationsverhalten. Zur
Manipulation der Fokussieroptik wird eine robotische Plattform realisiert. Diese basiert auf einem
lÀngenverÀnderlichen Kontinuumsmanipulator. Letzterer ermöglicht in Kombination mit einer
mechatronischen Aktuierungseinheit Bewegungen des Endoskopkopfes in fĂŒnf Freiheitsgraden.
Die kinematische Modellierung und Regelung des Systems werden in ein modulares Framework
eingebunden und evaluiert. Die Manipulation fokussierter Laserstrahlung erfordert zudem eine
prĂ€zise Anpassung der Fokuslage auf das Gewebe. DafĂŒr werden visuelle, haptische und visuell haptische Assistenzfunktionen eingefĂŒhrt. Diese unterstĂŒtzen den Anwender bei Teleoperation
zur Einstellung eines optimalen Arbeitsabstandes. In einer Anwenderstudie werden Vorteile der
visuell-haptischen Assistenz nachgewiesen. Die Systemperformanz und Gebrauchstauglichkeit
des robotischen Gesamtsystems werden in einer weiteren Anwenderstudie untersucht. Analog zu
einem klinischen Einsatz verfolgen die Probanden mit einem Laserspot vorgegebene Sollpfade. Die
mittlere Positioniergenauigkeit des Spots betrÀgt dabei 0,5 mm. Zur Automatisierung der Ablation
werden abschlieĂend Methoden der bildgestĂŒtzten Regelung vorgestellt. Experimente bestĂ€tigen
einen positiven Effekt der Automationskonzepte fĂŒr die kontaktfreie Laserchirurgie
Toward Bio-Inspired Tactile Sensing Capsule Endoscopy for Detection of Submucosal Tumors
© 2016 IEEE. Here, we present a method for lump characterization using a bio-inspired remote tactile sensing capsule endoscopy system. While current capsule endoscopy utilizes cameras to diagnose lesions on the surface of the gastrointestinal tract lumen, this proposal uses remote palpation to stimulate a bio-inspired tactile sensing surface that deforms under the impression of both hard and soft raised objects. Current capsule endoscopy utilizes cameras to visually diagnose lesions on the surface of the gastrointestinal tract. Our approach introduces remote palpation by deploying a bio-inspired tactile sensor that deforms when pressed against soft or hard lumps. This can enhance visual inspection of lesions and provide more information about the structure of the lesions. Using classifier systems, we have shown that lumps of different sizes, shapes, and hardnesses can be distinguished in a synthetic test environment. This is a promising early start toward achieving a remote palpation system used inside the GI tract that will utilize the clinician's sense of touch
Haptic robot-environment interaction for self-supervised learning in ground mobility
Dissertação para obtenção do Grau de Mestre em
Engenharia EletrotĂ©cnica e de ComputadoresThis dissertation presents a system for haptic interaction and self-supervised learning mechanisms to ascertain navigation affordances from depth cues. A simple pan-tilt telescopic arm and a structured light sensor, both fitted to the robotâs body frame, provide the required haptic and depth sensory feedback. The system aims at incrementally develop the ability to assess the cost of navigating in natural environments. For this purpose the robot learns a mapping between the appearance
of objects, given sensory data provided by the sensor, and their bendability, perceived by the pan-tilt telescopic arm. The object descriptor, representing the object in memory and used for comparisons with other objects, is rich for a robust comparison and simple enough to allow for fast computations.
The output of the memory learning mechanism allied with the haptic interaction point evaluation prioritize interaction points to increase the confidence on the interaction and correctly identifying obstacles,
reducing the risk of the robot getting stuck or damaged. If the system concludes that the
object is traversable, the environment change detection system allows the robot to overcome it. A set of field trials show the ability of the robot to progressively learn which elements of environment are traversable
Haptic feedback in teleoperation in Micro-and Nano-Worlds.
International audienceRobotic systems have been developed to handle very small objects, but their use remains complex and necessitates long-duration training. Simulators, such as molecular simulators, can provide access to large amounts of raw data, but only highly trained users can interpret the results of such systems. Haptic feedback in teleoperation, which provides force-feedback to an operator, appears to be a promising solution for interaction with such systems, as it allows intuitiveness and flexibility. However several issues arise while implementing teleoperation schemes at the micro-nanoscale, owing to complex force-fields that must be transmitted to users, and scaling differences between the haptic device and the manipulated objects. Major advances in such technology have been made in recent years. This chapter reviews the main systems in this area and highlights how some fundamental issues in teleoperation for micro- and nano-scale applications have been addressed. The chapter considers three types of teleoperation, including: (1) direct (manipulation of real objects); (2) virtual (use of simulators); and (3) augmented (combining real robotic systems and simulators). Remaining issues that must be addressed for further advances in teleoperation for micro-nanoworlds are also discussed, including: (1) comprehension of phenomena that dictate very small object (< 500 micrometers) behavior; and (2) design of intuitive 3-D manipulation systems. Design guidelines to realize an intuitive haptic feedback teleoperation system at the micro-nanoscale level are proposed
Voronoi Features for Tactile Sensing: Direct Inference of Pressure, Shear, and Contact Locations
There are a wide range of features that tactile contact provides, each with
different aspects of information that can be used for object grasping,
manipulation, and perception. In this paper inference of some key tactile
features, tip displacement, contact location, shear direction and magnitude, is
demonstrated by introducing a novel method of transducing a third dimension to
the sensor data via Voronoi tessellation. The inferred features are displayed
throughout the work in a new visualisation mode derived from the Voronoi
tessellation; these visualisations create easier interpretation of data from an
optical tactile sensor that measures local shear from displacement of internal
pins (the TacTip). The output values of tip displacement and shear magnitude
are calibrated to appropriate mechanical units and validate the direction of
shear inferred from the sensor. We show that these methods can infer the
direction of shear to 2.3 without the need for training a
classifier or regressor. The approach demonstrated here will increase the
versatility and generality of the sensors and thus allow sensor to be used in
more unstructured and unknown environments, as well as improve the use of these
tactile sensors in more complex systems such as robot hands.Comment: Presented at ICRA 201
Event-based Vision: A Survey
Event cameras are bio-inspired sensors that differ from conventional frame
cameras: Instead of capturing images at a fixed rate, they asynchronously
measure per-pixel brightness changes, and output a stream of events that encode
the time, location and sign of the brightness changes. Event cameras offer
attractive properties compared to traditional cameras: high temporal resolution
(in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low
power consumption, and high pixel bandwidth (on the order of kHz) resulting in
reduced motion blur. Hence, event cameras have a large potential for robotics
and computer vision in challenging scenarios for traditional cameras, such as
low-latency, high speed, and high dynamic range. However, novel methods are
required to process the unconventional output of these sensors in order to
unlock their potential. This paper provides a comprehensive overview of the
emerging field of event-based vision, with a focus on the applications and the
algorithms developed to unlock the outstanding properties of event cameras. We
present event cameras from their working principle, the actual sensors that are
available and the tasks that they have been used for, from low-level vision
(feature detection and tracking, optic flow, etc.) to high-level vision
(reconstruction, segmentation, recognition). We also discuss the techniques
developed to process events, including learning-based techniques, as well as
specialized processors for these novel sensors, such as spiking neural
networks. Additionally, we highlight the challenges that remain to be tackled
and the opportunities that lie ahead in the search for a more efficient,
bio-inspired way for machines to perceive and interact with the world
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Soft Morphological Computation
Soft Robotics is a relatively new area of research, where progress in material science has powered the next generation of robots, exhibiting biological-like properties such as soft/elastic tissues, compliance, resilience and more besides. One of the issues when employing soft robotics technologies is the soft nature of the interactions arising between the robot and its environment. These interactions are complex, and the their dynamics are non-linear and hard to capture with known models. In this thesis we argue that complex soft interactions
can actually be beneficial to the robot, and give rise to rich stimuli which can be used for the resolution of robot tasks. We further argue that the usefulness of these interactions depends on statistical regularities, or structure, that appear in the stimuli. To this end, robots should appropriately employ their morphology and their actions, to influence the system-environment interactions such that structure can arise in the stimuli. In this thesis we show that learning processes can be used to perform such a task. Following this rationale, this thesis proposes and supports the theory of Soft Morphological Computation (SoMComp), by which a soft robot should appropriately condition, or âaffectâ, the soft interactions to improve the quality of the physical stimuli arising from it. SoMComp is composed of four main principles, i.e.: Soft Proprioception, Soft Sensing, Soft Morphology and Soft Actuation. Each of these principles is explored in the context of haptic object recognition or object handling in soft robots. Finally, this thesis provides an overview of this research and its future directions.AHDB CP17
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