Eugenio Monari

dblp:353/5793 · DBLP profile ↗
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1ranked-venue papers
1as 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 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
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
null space optimization
0.712023
On Locally Optimal Redundancy Resolution using the Basis of the Null Space · ICRA 2023
Robotics › Motion planning and robot control
redundancy resolution
0.712023
On Locally Optimal Redundancy Resolution using the Basis of the Null Space · ICRA 2023

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

gradient projection · 0.7constrained optimization · 0.7
YearPublicationVenuePosition
2023 On Locally Optimal Redundancy Resolution using the Basis of the Null Space
abstract
This paper presents two methods for the computation of the null space velocity command in redundant robots. Both these methods resort to the solution of a constrained optimization problem. The first one is a formalization of the traditional Gradient Projection Method (GPM) which guarantees the respect of the joint bounds and a gradual activation/deactivation of the null space command. The second one, called Null Space Basis Optimal Linear Combination Method (NSBM), finds the optimal coefficients of a basis of the null space of the Jacobian, ensuring in turn that the joint bounds are respected and that the null space is activated and deactivated gradually. The two methods are applied to the case study of a welding application in which the null space command must avoid the collision between the robot and an obstacle. The comparison of the results of the case study shows that NSBM performs better than GPM. The proposed algorithms are also tested on a real robotic platform to demonstrate that their computational time is compatible with the real-time requirements of the robot.
Eugenio Monari, Rocco Vertechy
ICRA1