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Emanuele Morgavi

dblp:18/6707 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1999
—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
Motion planning and robot control · 56% Robot navigation and mapping · 36% Legged, aerial and field robots · 8%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping
obstacle avoidance
0.011999
Real-Time Path Planning and Obstacle Avoidance for an Autonomous Underwater Vehicle · ICRA 1999
Robotics › Motion planning and robot control
path planning
0.011999
Real-Time Path Planning and Obstacle Avoidance for an Autonomous Underwater Vehicle · ICRA 1999
Robotics › Motion planning and robot control › path planning
real-time path planning
0.011999
Real-Time Path Planning and Obstacle Avoidance for an Autonomous Underwater Vehicle · ICRA 1999
Robotics › Legged, aerial and field robots › underwater robotics
underwater vehicle control
0.011999
Real-Time Path Planning and Obstacle Avoidance for an Autonomous Underwater Vehicle · ICRA 1999
Robotics › Robot navigation and mapping › mobile robot navigation › vehicle navigation
underwater vehicle navigation
0.011999
Real-Time Path Planning and Obstacle Avoidance for an Autonomous Underwater Vehicle · ICRA 1999

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

visual pipeline tracking · 0.0ocean current compensation · 0.0
YearPublicationVenuePosition
1999 Real-Time Path Planning and Obstacle Avoidance for an Autonomous Underwater Vehicle
abstract
A navigation system for real-time path planning and obstacle avoidance of an autonomous underwater vehicle is presented. The vehicle is designed to accomplishing two missions: pre-deployment survey of sea bottom, and visual inspection of pipelines. In the first mission the navigation system must be able to track a predefined path while avoiding the unplanned occurrence of obstacles. In the second mission the navigation system must track a pipeline by locally reconstructing its location from visual information; also in this case, the unplanned occurrence of obstacles must be handled. Furthermore, the navigation system must properly take into account the presence of ocean current and some drastic constraints due to sensor and actuator characteristics.
Gianluca Antonelli, Stefano Chiaverini, Roberto Finotello, Emanuele Morgavi
ICRA4