2,760 research outputs found
Recent Developments in Aerial Robotics: A Survey and Prototypes Overview
In recent years, research and development in aerial robotics (i.e., unmanned
aerial vehicles, UAVs) has been growing at an unprecedented speed, and there is
a need to summarize the background, latest developments, and trends of UAV
research. Along with a general overview on the definition, types, categories,
and topics of UAV, this work describes a systematic way to identify 1,318
high-quality UAV papers from more than thirty thousand that have been appeared
in the top journals and conferences. On top of that, we provide a bird's-eye
view of UAV research since 2001 by summarizing various statistical information,
such as the year, type, and topic distribution of the UAV papers. We make our
survey list public and believe that the list can not only help researchers
identify, study, and compare their work, but is also useful for understanding
research trends in the field. From our survey results, we find there are many
types of UAV, and to the best of our knowledge, no literature has attempted to
summarize all types in one place. With our survey list, we explain the types
within our survey and outline the recent progress of each. We believe this
summary can enhance readers' understanding on the UAVs and inspire researchers
to propose new methods and new applications.Comment: 14 pages, 16 figures, typos correcte
Visual end-effector tracking using a 3D model-aided particle filter for humanoid robot platforms
This paper addresses recursive markerless estimation of a robot's
end-effector using visual observations from its cameras. The problem is
formulated into the Bayesian framework and addressed using Sequential Monte
Carlo (SMC) filtering. We use a 3D rendering engine and Computer Aided Design
(CAD) schematics of the robot to virtually create images from the robot's
camera viewpoints. These images are then used to extract information and
estimate the pose of the end-effector. To this aim, we developed a particle
filter for estimating the position and orientation of the robot's end-effector
using the Histogram of Oriented Gradient (HOG) descriptors to capture robust
characteristic features of shapes in both cameras and rendered images. We
implemented the algorithm on the iCub humanoid robot and employed it in a
closed-loop reaching scenario. We demonstrate that the tracking is robust to
clutter, allows compensating for errors in the robot kinematics and servoing
the arm in closed loop using vision
Fuzzy Logic of Speed and Steering Control System for Three Dimensional Line Following of an Autonomous Vehicle
... This paper is to describe exploratory research on the design of a modular
autonomous mobile robot controller. The controller incorporates a fuzzy logic
[8] [9] approach for steering and speed control [37], a FL approach for
ultrasound sensing and an overall expert system for guidance. The advantages of
a modular system are related to portability and transportability, i.e. any
vehicle can become autonomous with minimal modifications. A mobile robot test
bed has been constructed in university of Cincinnati using a golf cart base.
This cart has full speed control with guidance provided by a vision system and
obstacle avoidance using ultrasonic sensors. The speed and steering fuzzy logic
controller is supervised through a multi-axis motion controller. The obstacle
avoidance system is based on a microcontroller interfaced with ultrasonic
transducers. This micro-controller independently handles all timing and
distance calculations and sends distance information back to the fuzzy logic
controller via the serial line. This design yields a portable independent
system in which high speed computer communication is not necessary. Vision
guidance has been accomplished with the use of CCD cameras judging the current
position of the robot.[34] [35][36] It will be generating a good image for
reducing an uncertain wrong command from ground coordinate to tackle the
parameter uncertainties of the system, and to obtain good WMR dynamic
response.[1] Here we Apply 3D line following mythology. It transforms from 3D
to 2D and also maps the image coordinates and vice versa, leading to the
improved accuracy of the WMR position. ...Comment: IEEE Publication format, International Journal of Computer Science
and Information Security, IJCSIS, Vol. 7 No. 3, March 2010, USA. ISSN 1947
5500, http://sites.google.com/site/ijcsis
Quasi-Direct Drive for Low-Cost Compliant Robotic Manipulation
Robots must cost less and be force-controlled to enable widespread, safe
deployment in unconstrained human environments. We propose Quasi-Direct Drive
actuation as a capable paradigm for robotic force-controlled manipulation in
human environments at low-cost. Our prototype - Blue - is a human scale 7
Degree of Freedom arm with 2kg payload. Blue can cost less than $5000. We show
that Blue has dynamic properties that meet or exceed the needs of human
operators: the robot has a nominal position-control bandwidth of 7.5Hz and
repeatability within 4mm. We demonstrate a Virtual Reality based interface that
can be used as a method for telepresence and collecting robot training
demonstrations. Manufacturability, scaling, and potential use-cases for the
Blue system are also addressed. Videos and additional information can be found
online at berkeleyopenarms.github.ioComment: This is our long version - 8 pages. Our 6 page version without a
discussion of thermal limits was accepted to ICRA 2019. 11 Figure
Understanding Human Motion and Gestures for Underwater Human-Robot Collaboration
In this paper, we present a number of robust methodologies for an underwater
robot to visually detect, follow, and interact with a diver for collaborative
task execution. We design and develop two autonomous diver-following
algorithms, the first of which utilizes both spatial- and frequency-domain
features pertaining to human swimming patterns in order to visually track a
diver. The second algorithm uses a convolutional neural network-based model for
robust tracking-by-detection. In addition, we propose a hand gesture-based
human-robot communication framework that is syntactically simpler and
computationally more efficient than the existing grammar-based frameworks. In
the proposed interaction framework, deep visual detectors are used to provide
accurate hand gesture recognition; subsequently, a finite-state machine
performs robust and efficient gesture-to-instruction mapping. The
distinguishing feature of this framework is that it can be easily adopted by
divers for communicating with underwater robots without using artificial
markers or requiring memorization of complex language rules. Furthermore, we
validate the performance and effectiveness of the proposed methodologies
through extensive field experiments in closed- and open-water environments.
Finally, we perform a user interaction study to demonstrate the usability
benefits of our proposed interaction framework compared to existing methods.Comment: arXiv admin note: text overlap with arXiv:1709.0877
Adjustable impedance, force feedback and command language aids for telerobotics (parts 1-4 of an 8-part MIT progress report)
Projects recently completed or in progress at MIT Man-Machine Systems Laboratory are summarized. (1) A 2-part impedance network model of a single degree of freedom remote manipulation system is presented in which a human operator at the master port interacts with a task object at the slave port in a remote location is presented. (2) The extension of the predictor concept to include force feedback and dynamic modeling of the manipulator and the environment is addressed. (3) A system was constructed to infer intent from the operator's commands and the teleoperation context, and generalize this information to interpret future commands. (4) A command language system is being designed that is robust, easy to learn, and has more natural man-machine communication. A general telerobot problem selected as an important command language context is finding a collision-free path for a robot
What Communication Modalities Do Users Prefer in Real Time HRI?
This paper investigates users' preferred interaction modalities when playing
an imitation game with KASPAR, a small child-sized humanoid robot. The study
involved 16 adult participants teaching the robot to mime a nursery rhyme via
one of three interaction modalities in a real-time Human-Robot Interaction
(HRI) experiment: voice, guiding touch and visual demonstration. The findings
suggest that the users appeared to have no preference in terms of human effort
for completing the task. However, there was a significant difference in human
enjoyment preferences of input modality and a marginal difference in the
robot's perceived ability to imitate.Comment: 5th International Symposium on New Frontiers in Human-Robot
Interaction 2016 (arXiv:1602.05456
Visual servoing
Master'sMASTER OF ENGINEERIN
Towards a Framework for Embodying Any-Body through Sensory Translation and Proprioceptive Remapping: A Pilot Study
We address the problem of physical avatar embodiment and investi-
gate the most general factors that may allow a person to “wear” an-
other body, different from her own. A general approach is required
to exploit the fact that an avatar can have any kind of body. With
this pilot study we introduce a conceptual framework for the design
of non-anthropomorphic embodiment, to foster immersion and
user engagement. The person is interfaced with the avatar, a robot,
through a system that induces a divergent internal sensorimotor
mapping while controlling the avatar, to create an immersive expe-
rience. Together with the conceptual framework, we present two
implementations: a prototype tested in the lab and an interactive in-
stallation exhibited to general public. These implementations consist
of a wheeled robot, and control and sensory feedback systems. The
control system includes mechanisms that both detect and resist the
user’s movement, increasing the sense of connection with the avatar;
the feedback system is a virtual reality (VR) environment represent-
ing the avatar’s unique perception, combining sensor and control in-
formation to generate visual cues. Data gathered from users indicate
that the systems implemented following the proposed framework
create a challenging and engaging experience, thus providing solid
ground for further developments
Compare Contact Model-based Control and Contact Model-free Learning: A Survey of Robotic Peg-in-hole Assembly Strategies
In this paper, we present an overview of robotic peg-in-hole assembly and
analyze two main strategies: contact model-based and contact model-free
strategies. More specifically, we first introduce the contact model control
approaches, including contact state recognition and compliant control two
steps. Additionally, we focus on a comprehensive analysis of the whole robotic
assembly system. Second, without the contact state recognition process, we
decompose the contact model-free learning algorithms into two main subfields:
learning from demonstrations and learning from environments (mainly based on
reinforcement learning). For each subfield, we survey the landmark studies and
ongoing research to compare the different categories. We hope to strengthen the
relation between these two research communities by revealing the underlying
links. Ultimately, the remaining challenges and open questions in the field of
robotic peg-in-hole assembly community is discussed. The promising directions
and potential future work are also considered
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