Anagh Lal

dblp:94/5909 · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2005
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 1 first-authorSystems, architecture and hardware · 2Graphics, computer vision, multimedia, augmented reality and games · 2 · 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
2 papers
Knowledge representation and reasoning · 57% Planning, search and constraint satisfaction · 43%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › constraint satisfaction
interchangeability
0.112005
Neighborhood Interchangeability and Dynamic Bundling for Non-Binary Finite CSPs · AAAI 2005
Knowledge, reasoning and agents › Knowledge representation and reasoning › temporal reasoning
temporal constraint satisfaction
0.012004
Evaluating Consistency Algorithms for Temporal Metric Constraints · AAAI 2004
Knowledge, reasoning and agents › Knowledge representation and reasoning
temporal reasoning
0.012004
Evaluating Consistency Algorithms for Temporal Metric Constraints · AAAI 2004

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

consistency algorithms · 0.0
YearPublicationVenuePosition
2005 Neighborhood Interchangeability and Dynamic Bundling for Non-Binary Finite CSPs
Anagh Lal, Berthe Y. Choueiry, Eugene C. Freuder
AAAI1
2005 Global Control of Robotic Highway Safety Markers: A Real-time Solution
Jiazheng Shi, Steve Goddard, Anagh Lal, Jason Dumpert, Shane Farritor
Real Time Syst.3
2004 Evaluating Consistency Algorithms for Temporal Metric Constraints
Anagh Lal, Berthe Y. Choueiry
AAAI2
2004 A Real-Time Model for the Robotic Highway Safety Marker System
abstract
We present the design and implementation of a real-time model for the global control of robotic highway safety markers. Problems addressed in the system are: 1) poor scalability and predictability as the number of markers increases, 2) jerky movement of markers, and 3) false-hits caused by environment objects. We extensively analyze the system and offer two solutions: a basic solution and an enhanced solution. They are built respectively upon two task models: the periodic task model and the variable rate execution task model. The former is characterized by four static parameters: phase, period, worst case execution time and relative deadline. The latter has similar parameters. Its parameter values, however, are allowed to change at arbitrary times. We then examine two typical real-time scheduling approaches: rate monotonic (RM) priority driven and earliest deadline first (EDF). Analysis of their sufficient conditions shows that our system is feasibly schedulable under either RM or EDF. This conclusion justifies that the path for each safety marker can be guaranteed to be smooth under the designed real-time system. For the scalability issue, we present a sufficient condition for the upper bound on the number of barrel robots that can be reliably controlled. One key technique integrated into our real-time system is the Hough transform. We refine its traditional implementation so that, for the task of detecting safety markers, the time complexity decreases and the reliability increases with only slight additional storage for search windows. The basic idea behind our improvements is to limit the search window for safety markers.
Jiazheng Shi, Steve Goddard, Anagh Lal, Shane Farritor
IEEE Real-Time and Embedded Technology and Applications Symposium3