2,212 research outputs found
Human operator performance of remotely controlled tasks: Teleoperator research conducted at NASA's George C. Marshal Space Flight Center
The capabilities within the teleoperator laboratories to perform remote and teleoperated investigations for a wide variety of applications are described. Three major teleoperator issues are addressed: the human operator, the remote control and effecting subsystems, and the human/machine system performance results for specific teleoperated tasks
Supervised Autonomous Locomotion and Manipulation for Disaster Response with a Centaur-like Robot
Mobile manipulation tasks are one of the key challenges in the field of
search and rescue (SAR) robotics requiring robots with flexible locomotion and
manipulation abilities. Since the tasks are mostly unknown in advance, the
robot has to adapt to a wide variety of terrains and workspaces during a
mission. The centaur-like robot Centauro has a hybrid legged-wheeled base and
an anthropomorphic upper body to carry out complex tasks in environments too
dangerous for humans. Due to its high number of degrees of freedom, controlling
the robot with direct teleoperation approaches is challenging and exhausting.
Supervised autonomy approaches are promising to increase quality and speed of
control while keeping the flexibility to solve unknown tasks. We developed a
set of operator assistance functionalities with different levels of autonomy to
control the robot for challenging locomotion and manipulation tasks. The
integrated system was evaluated in disaster response scenarios and showed
promising performance.Comment: In Proceedings of IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS), Madrid, Spain, October 201
Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 314)
This bibliography lists 139 reports, articles, and other documents introduced into the NASA scientific and technical information system in August, 1988
3D measurements in conventional X-ray imaging with RGB-D sensors
[EN] A method for deriving 3D internal information in conventional X-ray settings is presented. It is based on the combination of a pair of radiographs from a patient and it avoids the use of X-ray-opaque fiducials and external reference structures. To achieve this goal, we augment an ordinary X-ray device with a consumer RGB-D camera. The patient' s rotation around the craniocaudal axis is tracked relative to this camera thanks to the depth information provided and the application of a modern surface-mapping algorithm. The measured spatial information is then translated to the reference frame of the X-ray imaging system. By using the intrinsic parameters of the diagnostic equipment, epipolar geometry, and X-ray images of the patient at different angles, 3D internal positions can be obtained. Both the RGB-D and Xray instruments are first geometrically calibrated to find their joint spatial transformation. The proposed method is applied to three rotating phantoms. The first two consist of an anthropomorphic head and a torso, which are filled with spherical lead bearings at precise locations. The third one is made of simple foam and has metal needles of several known lengths embedded in it. The results show that it is possible to resolve anatomical positions and lengths with a millimetric level of precision. With the proposed approach, internal 3D reconstructed coordinates and distances can be provided to the physician. It also contributes to reducing the invasiveness of ordinary X-ray environments and can replace other types of clinical explorations that are mainly aimed at measuring or geometrically relating elements that are present inside the patient's body.(C) 2017 IPEM. Published by Elsevier Ltd. All rights reserved.The authors would like to thank the Radiation Oncology Department of the Physics Section at La Fe Hospital for the anthropomorphic phantom used in this work and Jose Manuel Monserrate (Instituto de Física Corpuscular) for his contribution in the development of the calibration frame shown in Fig. 3. This research has the support of Information Storage S.L., University of Valencia (grant CPI-15-170), CSD-2007-00042 Con solider Ingenio CPAN (grant CPAN-13TR01), IFIC (Severo Ochoa Centre of Excellence SEV20140398) as well as the support of the Spanish Ministry of Industry, Energy, and Tourism (grant TSI1001012013019).Albiol Colomer, F.; Corbi, A.; Albiol Colomer, A. (2017). 3D measurements in conventional X-ray imaging with RGB-D sensors. Medical Engineering & Physics. 42:73-79. https://doi.org/10.1016/j.medengphy.2017.01.024S73794
Independent Motion Detection with Event-driven Cameras
Unlike standard cameras that send intensity images at a constant frame rate,
event-driven cameras asynchronously report pixel-level brightness changes,
offering low latency and high temporal resolution (both in the order of
micro-seconds). As such, they have great potential for fast and low power
vision algorithms for robots. Visual tracking, for example, is easily achieved
even for very fast stimuli, as only moving objects cause brightness changes.
However, cameras mounted on a moving robot are typically non-stationary and the
same tracking problem becomes confounded by background clutter events due to
the robot ego-motion. In this paper, we propose a method for segmenting the
motion of an independently moving object for event-driven cameras. Our method
detects and tracks corners in the event stream and learns the statistics of
their motion as a function of the robot's joint velocities when no
independently moving objects are present. During robot operation, independently
moving objects are identified by discrepancies between the predicted corner
velocities from ego-motion and the measured corner velocities. We validate the
algorithm on data collected from the neuromorphic iCub robot. We achieve a
precision of ~ 90 % and show that the method is robust to changes in speed of
both the head and the target.Comment: 7 pages, 6 figure
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
Integration of Absolute Orientation Measurements in the KinectFusion Reconstruction pipeline
In this paper, we show how absolute orientation measurements provided by
low-cost but high-fidelity IMU sensors can be integrated into the KinectFusion
pipeline. We show that integration improves both runtime, robustness and
quality of the 3D reconstruction. In particular, we use this orientation data
to seed and regularize the ICP registration technique. We also present a
technique to filter the pairs of 3D matched points based on the distribution of
their distances. This filter is implemented efficiently on the GPU. Estimating
the distribution of the distances helps control the number of iterations
necessary for the convergence of the ICP algorithm. Finally, we show
experimental results that highlight improvements in robustness, a speed-up of
almost 12%, and a gain in tracking quality of 53% for the ATE metric on the
Freiburg benchmark.Comment: CVPR Workshop on Visual Odometry and Computer Vision Applications
Based on Location Clues 201
Manipulator system man-machine interface evaluation program
Application and requirements for remote manipulator systems for future space missions were investigated. A manipulator evaluation program was established to study the effects of various systems parameters on operator performance of tasks necessary for remotely manned missions. The program and laboratory facilities are described. Evaluation criteria and philosophy are discussed
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