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Evan Palmer

dblp:217/6604 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021

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 · 87% Motion planning and robot control · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
underwater robotics
0.812024
Angler: An Autonomy Framework for Intervention Tasks with Lightweight Underwater Vehicle Manipulator Systems · ICRA 2024
Robotics › Legged, aerial and field robots › underwater robotics
underwater vehicle-manipulator system
0.812024
Angler: An Autonomy Framework for Intervention Tasks with Lightweight Underwater Vehicle Manipulator Systems · ICRA 2024

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

waypoint tracking · 0.8station keeping · 0.8sim-to-real transfer · 0.8
YearPublicationVenuePosition
2024 Angler: An Autonomy Framework for Intervention Tasks with Lightweight Underwater Vehicle Manipulator Systems
abstract
Developing autonomous intervention capabilities for lightweight underwater vehicle manipulator systems (UVMS) has garnered significant attention within recent years because of the opportunity for these systems to reduce intervention operating costs. Developing autonomous UVMS capabilities is challenging, however, because of the lack of available standardized software frameworks and pipelines. Previous works offer simulation environments and deployment pipelines for underwater vehicles, but fall short of providing a complete UVMS software framework. We address this gap by creating Angler: a software framework for developing localization, control, and decision-making algorithms with support for sim-to-real transfer. We validate this framework by implementing a state-of-the-art control architecture and demonstrate the ability to perform station keeping with a mean error below 0.25 m and waypoint tracking with an average final error of 0.398 m.
Evan Palmer, Christopher Holm, Geoffrey A. Hollinger
ICRA1