Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Tanya Lippincott

dblp:126/2579 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 1997
—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
Robot navigation and mapping · 67% Planning, search and constraint satisfaction · 33%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping › mobile robot navigation › reactive navigation
behavior-based navigation
0.011997
Adaptive fuzzy-behavior hierarchy for autonomous navigation · ICRA 1997
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › intelligent control
fuzzy control
0.011997
Adaptive fuzzy-behavior hierarchy for autonomous navigation · ICRA 1997
Robotics › Robot navigation and mapping
mobile robot navigation
0.011997
Adaptive fuzzy-behavior hierarchy for autonomous navigation · ICRA 1997

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

fuzzy logic · 0.0behavior-based architecture · 0.0
YearPublicationVenuePosition
1997 Adaptive fuzzy-behavior hierarchy for autonomous navigation
abstract
Adaptive behavioral capabilities are necessary for robust navigation in non-engineered environments. A control approach to adaptive behavior is described which exploits the approximate reasoning facility of fuzzy logic. In particular, a behavior-based architecture for hierarchical fuzzy control of mobile robots is presented. Its structure is described as well as mechanisms of control decision-making which give rise to adaptive behavior. Control decisions result from a consensus of recommendations offered only by behaviors that are applicable to current situations. Indoor navigation examples demonstrate the practicality of the approach and reveals characteristics of multiple behavior interaction.
Edward W. Tunstel, Harrison Danny, Tanya Lippincott, Mo Jamshidi 0001
ICRA3