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Jonathan Klein Schiphorst

dblp:366/1964 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 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
Robot navigation and mapping · 60% Legged, aerial and field robots · 40%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping › docking
autonomous docking
0.612022
Design of an Autonomous Latching System for Surface Vessels · ICRA 2022
Robotics › Legged, aerial and field robots › field robotics › maritime robotics
autonomous surface vehicle
0.612022
Design of an Autonomous Latching System for Surface Vessels · ICRA 2022
Robotics › Robot navigation and mapping
docking
0.612022
Design of an Autonomous Latching System for Surface Vessels · ICRA 2022
Robotics › Legged, aerial and field robots
underwater robotics
0.612022
Design of an Autonomous Latching System for Surface Vessels · ICRA 2022
Robotics › Robot navigation and mapping › docking
vision-based docking
0.612022
Design of an Autonomous Latching System for Surface Vessels · ICRA 2022

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

mechanical latching · 0.6computer vision · 0.6
YearPublicationVenuePosition
2022 Design of an Autonomous Latching System for Surface Vessels
abstract
Autonomous latching is essential for autonomous surface vessels (ASV) to reach full independence from human intervention. As part of the ASV Roboat project, a new solution for self-latching maneuvers has been developed and is presented here. We propose a system that has the key requirements of full integration with the navigation control system and zero-gap connection with the dock, the latter being essential for wireless charging of the ASV. Dedicated markers are used to identify docking targets, relying on computer vision algorithms to determine distance and bearing to the target. In its idle state, the locking solution uses mechanical power-off brakes, minimizing energy consumption while ensuring the boat stays in position indefinitely once docked. A prototype of the proposed mechanism has been built and installed in Roboat. Experimental tests showing the mechanism performance and capability to autonomously approach the docking station are discussed in this work.
David Fernández-Gutiérrez, Niklas Hagemann, Wei Wang 0078, Rens M. Doornbusch, Joshua Jordan, Jonathan Klein Schiphorst, Pietro Leoni, Fabio Duarte, Carlo Ratti, Daniela Rus
ICRA6