(Georgia Institute of Technology, 2016-05)
Park, Daehyung; Kim, You Keun; Erickson, Zackory; Kemp, Charles C.
General-purpose mobile manipulators have the
potential to serve as a versatile form of assistive technology.
However, their complexity creates challenges, including the risk
of being too difficult to use. We present a proof-of-concept
robotic system for assistive feeding that consists of a Willow
Garage PR2, a high-level web-based interface, and specialized
autonomous behaviors for scooping and feeding yogurt. As a
step towards use by people with disabilities, we evaluated our
system with 5 able-bodied participants. All 5 successfully ate
yogurt using the system and reported high rates of success
for the system’s autonomous behaviors. Also, Henry Evans, a
person with severe quadriplegia, operated the system remotely
to feed an able-bodied person. In general, people who operated
the system reported that it was easy to use, including Henry.
The feeding system also incorporates corrective actions designed
to be triggered either autonomously or by the user. In an
offline evaluation using data collected with the feeding system,
a new version of our multimodal anomaly detection system
outperformed prior versions.
(Georgia Institute of Technology, 2013-11)
Ta, Duy-Nguyen; Ok, Kyel; Dellaert, Frank
Despite recent progress, autonomous navigation
on Micro Aerial Vehicles with a single frontal camera is still
a challenging problem, especially in feature-lacking environ-
ments. On a mobile robot with a frontal camera, monoSLAM
can fail when there are not enough visual features in the scene,
or when the robot, with rotationally dominant motions, yaws
away from a known map toward unknown regions. To overcome
such limitations and increase responsiveness, we present a
novel parallel tracking and mapping framework that is suitable
for robot navigation by fusing visual data with odometry
measurements in a principled manner. Our framework can
cope with a lack of visual features in the scene, and maintain
robustness during pure camera rotations. We demonstrate our
results on a dataset captured from the frontal camera of a quad-
rotor flying in a typical feature-lacking indoor environment.