| dc.description.abstract | In the near future robotics will become a much larger part of our
society, and more robots will be developed to execute a range of gen-
eral tasks, so that they are able to assist human operators in their
day to day work. At the Technical University of Eindhoven (TU/e),
the AMIGO robot is designed to perform such general service tasks,
with a special focus on health care applications. A general purpose
service robot, such as AMIGO, needs a certain skill set to perform
tasks autonomously. One of these skills, is being able to perceive ob-
jects in the world. Using this information AMIGO can act accordingly,
e. g., by bringing the required object back to its operator.
This thesis describes a system for detecting household objects in
domestic environments. The object detection system has been devel-
oped for AMIGO, and is based on the object detection method, LINE-
MOD, presented by hinterstoisser et al. [1]. To make the system appli-
cable for both the general service tasks performed by AMIGO and the
RoboCup competition, an annual event encouraging robotic research,
LINE-MOD is extended by adding extra color modalities to the detec-
tion system, testing different normal extraction routines and enabling
the use of additional features. The detection module is subsequently
included in a framework with a different set of tools, making it of
practical use for the AMIGO project and its users, and is integrated
with existing systems used currently used in the AMIGO project. The
detection module is evaluated with household objects that AMIGO
encounters while performing service related tasks and competing in
the RoboCup competition.
The system is discovered to be able to recognize most household
objects with reasonable accuracy, the use of an added color modality
results in the increased accuracy of the detection of household objects
at a small performance penalty. However, it may still fail in situations
where objects are highly textured, resulting in false positives inside
object instances, and when object models are too similar in shape
or color a problem which is primarily caused by the use of highly
quantized feature types. | |
