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

S. Sabbadini

dblp:353/5902 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2023
—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
Motion planning and robot control · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
robot control
0.712023
Trajectory error compensation for optimal control of UMA-2 - a climbing robot executing maintenance operation in harsh environment · ICRA 2023
Robotics › Motion planning and robot control › mobile robot control
climbing robot control
0.212023
Trajectory error compensation for optimal control of UMA-2 - a climbing robot executing maintenance operation in harsh environment · ICRA 2023

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

trajectory analysis · 0.7adaptation model · 0.7
YearPublicationVenuePosition
2023 Trajectory error compensation for optimal control of UMA-2 - a climbing robot executing maintenance operation in harsh environment
abstract
UMA-2 is a wheeled mobile platform equipped with a vacuum adhesion system, eight actuated joints and four passive ones, designed to climb vertical and curved surfaces. The platform can perform maintenance tasks such as corrosion removal and cleaning with grinding while climbing. The quality of the repairing process is largely affected by grinding process parameters including tool forces, toolpath and the robot trajectory accuracy. The current work introduces a trajectory analysis and adaptation model to control the UMA-2 platform to ensure specific surface quality KPIs and incorporating the effects of robot compliancy. The proposed trajectory analysis has been extensively validated through experimental campaigns representative of maintenance in wind power industry.
Diego Gitardi, S. Sabbadini, Anna Valente
ICRA2