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

Neil Rugg-Gunn

dblp:54/1385 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
0since 2021 · last 1994
—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 · 67% Autonomous driving · 33%
Theoretical computer science
1 paper
Logic in computer science · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Autonomous driving
multi-vehicle coordination
0.011994
A Formal Semantics for Multiple Vehicle Task and Motion Planning · ICRA 1994
Robotics › Motion planning and robot control
path planning
0.011994
A Formal Semantics for Multiple Vehicle Task and Motion Planning · ICRA 1994
Robotics › Motion planning and robot control
task and motion planning
0.011994
A Formal Semantics for Multiple Vehicle Task and Motion Planning · ICRA 1994
Logic in computer science › semantics
denotational semantics
0.011994
A Formal Semantics for Multiple Vehicle Task and Motion Planning · ICRA 1994

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

timed traces · 0.0denotational semantics · 0.0
YearPublicationVenuePosition
1994 A Formal Semantics for Multiple Vehicle Task and Motion Planning
abstract
The application of autonomous guided vehicles to well-structured industrial sites requires considerably more than a path planning algorithm onboard each vehicle. Issues such as task planning, vehicle routing and vehicle-vehicle interactions predominate in determining the overall system ability. We exhibit a mathematical model of a multiple vehicle system, which has similarities to the Timed Traces models developed to reason about parallel processes. A denotational semantics is derived from this model, ascribing meaning to a simple language of service operations and concurrent path planning. This semantics captures a complete description of vehicles' behaviour, which can provide a global planning strategy guaranteeing both satisfiability and liveness.>
Neil Rugg-Gunn, Stephen Cameron
ICRA1