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

Merlin Morlock

dblp:353/5931 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved

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 manipulation · 70% Motion planning and robot control · 30%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
collision detection
0.712023
Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a Cobot · ICRA 2023
Robotics › Robot manipulation › tactile sensing › contact sensing
contact localization
0.712023
Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a Cobot · ICRA 2023
Robotics › Robot manipulation
physical human-robot interaction
0.712023
Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a Cobot · ICRA 2023
Robotics › Robot manipulation › industrial robot
collaborative robot
0.212023
Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a Cobot · ICRA 2023

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

particle filter · 0.7generalized momentum observer · 0.7energy monitoring · 0.7
YearPublicationVenuePosition
2023 Collision Detection and Contact Point Estimation Using Virtual Joint Torque Sensing Applied to a Cobot
abstract
In physical human-robot interaction (pHRI) it is essential to reliably estimate and localize contact forces between the robot and the environment. In this paper, a complete contact detection, isolation, and reaction scheme is presented and tested on a new 6-dof industrial collaborative robot. We combine two popular methods, based on monitoring energy and generalized momentum, to detect and isolate collisions on the whole robot body in a more robust way. The experimental results show the effectiveness of our implementation on the LARA 5 cobot, that only relies on motor current and joint encoder measurements. For validation purposes, contact forces are also measured using an external GTE CoboSafe sensor. After a successful collision detection, the contact point location is isolated using a combination of the residual method based on the generalized momentum with a contact particle filter (CPF) scheme. We show for the first time a successful implementation of such combination on a real robot, without relying on joint torque sensor measurements.
Dario Zurlo, Tom Heitmann, Merlin Morlock, Alessandro De Luca 0001
ICRA3