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

Alex C.-C. Meng

dblp:32/2808 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
0since 2021 · last 1988
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

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
Motion planning and robot control · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › path planning
collision-free path planning
0.011988
Dynamic motion replanning for unexpected obstacles · ICRA 1988
Robotics › Motion planning and robot control › motion planning › replanning
dynamic replanning
0.011988
Dynamic motion replanning for unexpected obstacles · ICRA 1988
Robotics › Motion planning and robot control
motion planning
0.011988
Dynamic motion replanning for unexpected obstacles · ICRA 1988

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

visibility graph · 0.0retraction method · 0.0local world model patching · 0.0
YearPublicationVenuePosition
1988 Dynamic motion replanning for unexpected obstacles
abstract
Motion-planning problems are discussed for a mobile robot with an incomplete map. For the given start and goal positions, the robot will preplan a collision-free path based on the given map, this is known as the find-path problem. A solution of the find-path problem is presented for randomly shaped obstacles using an improved retraction method, namely, retraction with local replacement by visibility graph. Three different versions of a motion replanning algorithm are presented that patch the world model and regenerate a path from the current location to the goal location. In this scheme, the recomputation of a completely updated world model is avoided by patching the locally updated environment.>
Alex C.-C. Meng
ICRA1