49,659 research outputs found
An Omnidirectional Aerial Manipulation Platform for Contact-Based Inspection
This paper presents an omnidirectional aerial manipulation platform for
robust and responsive interaction with unstructured environments, toward the
goal of contact-based inspection. The fully actuated tilt-rotor aerial system
is equipped with a rigidly mounted end-effector, and is able to exert a 6
degree of freedom force and torque, decoupling the system's translational and
rotational dynamics, and enabling precise interaction with the environment
while maintaining stability. An impedance controller with selective apparent
inertia is formulated to permit compliance in certain degrees of freedom while
achieving precise trajectory tracking and disturbance rejection in others.
Experiments demonstrate disturbance rejection, push-and-slide interaction, and
on-board state estimation with depth servoing to interact with local surfaces.
The system is also validated as a tool for contact-based non-destructive
testing of concrete infrastructure.Comment: Accepted submission to Robotics: Science and Systems conference 2019.
9 pages, 12 figure
Learning to Navigate Cloth using Haptics
We present a controller that allows an arm-like manipulator to navigate
deformable cloth garments in simulation through the use of haptic information.
The main challenge of such a controller is to avoid getting tangled in, tearing
or punching through the deforming cloth. Our controller aggregates force
information from a number of haptic-sensing spheres all along the manipulator
for guidance. Based on haptic forces, each individual sphere updates its target
location, and the conflicts that arise between this set of desired positions is
resolved by solving an inverse kinematic problem with constraints.
Reinforcement learning is used to train the controller for a single
haptic-sensing sphere, where a training run is terminated (and thus penalized)
when large forces are detected due to contact between the sphere and a
simplified model of the cloth. In simulation, we demonstrate successful
navigation of a robotic arm through a variety of garments, including an
isolated sleeve, a jacket, a shirt, and shorts. Our controller out-performs two
baseline controllers: one without haptics and another that was trained based on
large forces between the sphere and cloth, but without early termination.Comment: Supplementary video available at https://youtu.be/iHqwZPKVd4A.
Related publications http://www.cc.gatech.edu/~karenliu/Robotic_dressing.htm
Recovery of spinning satellites
The behavior of a space tug and a spinning satellite in a coupled configuration was simulated and analyzed. A docking concept was developed to investigate the requirements pertaining to the design of a docking interface. Sensing techniques and control requirements for the chase vehicle were studied to assess the feasibility of an automatic docking. The effects of nutation dampers and liquid propellant slosh motion upon the docking transient were investigated
Robot Composite Learning and the Nunchaku Flipping Challenge
Advanced motor skills are essential for robots to physically coexist with
humans. Much research on robot dynamics and control has achieved success on
hyper robot motor capabilities, but mostly through heavily case-specific
engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous
manner, robot learning from human demonstration (LfD) has achieved great
progress, but still has limitations handling dynamic skills and compound
actions. In this paper, we present a composite learning scheme which goes
beyond LfD and integrates robot learning from human definition, demonstration,
and evaluation. The method tackles advanced motor skills that require dynamic
time-critical maneuver, complex contact control, and handling partly soft
partly rigid objects. We also introduce the "nunchaku flipping challenge", an
extreme test that puts hard requirements to all these three aspects. Continued
from our previous presentations, this paper introduces the latest update of the
composite learning scheme and the physical success of the nunchaku flipping
challenge
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