H. Haffner

dblp:32/3571 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1998
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Legged, aerial and field robots · 67% Reinforcement learning · 33%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Reinforcement learning
exploration
0.011998
Experiences with the Development of a Robot for Smart Multisensoric Pipe Inspection · ICRA 1998
Robotics › Legged, aerial and field robots
field robotics
0.011998
Experiences with the Development of a Robot for Smart Multisensoric Pipe Inspection · ICRA 1998
Robotics › Legged, aerial and field robots › field robotics › pipeline robotics
pipeline inspection robot
0.011998
Experiences with the Development of a Robot for Smart Multisensoric Pipe Inspection · ICRA 1998

Methods — techniques the papers use, named apart from their topics

ultrasonic sensing · 0.0microwave sensing · 0.0fuzzy logic · 0.03d-optical sensing · 0.0
YearPublicationVenuePosition
1998 Experiences with the Development of a Robot for Smart Multisensoric Pipe Inspection
abstract
Up to 20 percent of the German sewerage systems are damaged mainly due to their high age. The estimation for the restoration costs is about 100 billions DM. As a consequence the German Government has issued comparably harsh environmental laws enforcing the owner of a sewerage system to check regularily its state by means of suitable inspection technology. However, at the present state of the art the inspection systems available on the market which are dominated by rather simple TV technology can not sufficiently comply with the qualified inspection demands. For closing this gap, in a joint R&D project with 4 partners from industry and research institutes the advanced multisensor robot inspection system KARO has been developed and prototypically realized which is able to detect automatically type, location and size of damages in the sewerage system. The modular system concept comprises both a high-resolution color TV camera and a multisensor system consisting of innovative 3D-optical, ultrasonic and microwave sensors. Thus, the robot is enabled online to detect and classify anomalies during the robot motion within the pipe or the pipe wall respectively as well as within the closer pipe surroundings. Moreover, the robot optionally comprises a navigation sensor module for exploration of a priori unknown sewerage topology during the robot motion. For sensor fusion and damage classification a new fuzzy based concept is applied.
Helge-Björn Kuntze, H. Haffner
ICRA2