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Alessio Margan

dblp:151/9269 · DBLP profile ↗
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3ranked-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 · 3 · 1 since 2021Systems, architecture and hardware · 3 · 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
2 papers
Robot manipulation · 63% Motion planning and robot control · 37%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › robot design
manipulator design
0.712023
Design and Validation of a Multi-Arm Relocatable Manipulator for Space Applications · ICRA 2023
Robotics › Robot manipulation
robot design
0.712023
Design and Validation of a Multi-Arm Relocatable Manipulator for Space Applications · ICRA 2023
Robotics › Motion planning and robot control › robot control › model-based control
computed torque control
0.212023
Design and Validation of a Multi-Arm Relocatable Manipulator for Space Applications · ICRA 2023
Robotics › Motion planning and robot control
trajectory optimization
0.212023
Design and Validation of a Multi-Arm Relocatable Manipulator for Space Applications · ICRA 2023
Robotics › Motion planning and robot control › robot control
compliant motion control
0.212014
Physical interaction detection and control of compliant manipulators equipped with friction clutches · ICRA 2014
Robotics › Motion planning and robot control › robot control › hybrid control
mode switching control
0.212014
Physical interaction detection and control of compliant manipulators equipped with friction clutches · ICRA 2014

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

sampling-based planning · 0.7quadratic programming · 0.7nonlinear trajectory optimization · 0.7friction torque modulation · 0.2
YearPublicationVenuePosition
2023 Design and Validation of a Multi-Arm Relocatable Manipulator for Space Applications
abstract
This work presents the computational design and validation of the Multi-Arm Relocatable Manipulator (MARM), a three-limb robot for space applications, with particular reference to the MIRROR (i.e., the Multi-arm Installation Robot for Readying ORUs and Reflectors) use-case scenario as proposed by the European Space Agency. A holistic computational design and validation pipeline is proposed, with the aim of comparing different limb designs, as well as ensuring that valid limb candidates enable MARM to perform the complex loco-manipulation tasks required. Moti-vated by the task complexity in terms of kinematic reachability, (self)-collision avoidance, contact wrench limits, and motor torque limits affecting Earth experiments, this work leverages on multiple state-of-art planning and control approaches to aid the robot design and validation. These include sampling-based planning on manifolds, non-linear trajectory optimization, and quadratic programs for inverse dynamics computations with constraints. Finally, we present the attained MARM design and conduct preliminary tests for hardware validation through a set of lab experiments.
Enrico Mingo Hoffman, Arturo Laurenzi, Francesco Ruscelli, Luca Rossini, Lorenzo Baccelliere, Davide Antonucci, Alessio Margan, Paolo Guria, Marco Migliorini, Stefano Cordasco, Gennaro Raiola, Luca Muratore, Joaquín Estremera Rodrigo, Andrea Rusconi, Guido Sangiovanni, Nikolaos G. Tsagarakis
ICRA7
2017 Development of a human size and strength compliant bi-manual platform for realistic heavy manipulation tasks
abstract
Developing a high physical performance robotic manipulation platform with considerable power density, strength and resilience is not a trivial task and frequently leads to heavy and bulky systems unable to meet the application requirements, i.e. such robots should have human body size compatibility to work in infrastructures designed for humans. In this work we present a new high performance human size and weight compatible bi-manual manipulation platform that demonstrates notable physical strength and power capabilities. To attain this performance, design features including custom high performance elastic drives and robust light weight structure principles were considered resulting in large payload to robot mass ratio that is greater than 1.5 for short time heavy payloads. The design principles and mechanics of the upper body bi-manual robot are presented providing details on the solutions adopted for the various mechatronics components. The performance of the system actuation and the strength capacity of the overall platform is verified through the execution of heavy payload motion and impact experiments.
Lorenzo Baccelliere, Navvab Kashiri, Luca Muratore, Arturo Laurenzi, Malgorzata Kamedula, Alessio Margan, Stefano Cordasco, Jörn Malzahn, Nikolaos G. Tsagarakis
IROS6
2014 Physical interaction detection and control of compliant manipulators equipped with friction clutches
abstract
This work focuses on the modeling and control of robotic manipulators powered by compliant actuation systems equipped with clutches for providing friction torque on demand. A novel control scheme is proposed for modulating the clutch friction torque in this particular class of compliant actuators to make the robot operate in “Rigid mode” when it does not interact with the environment to achieve high accuracy, bandwidth and controllability; meanwhile ensuring that the robot maximum static force is constrained to a maximum threshold permitting flexible reactions in potentially risky scenarios. The robot autonomously switches to “Compliant mode” (clutches off) when it interacts with external agents to exploit the advantages of compliance during contacts. Experimental results are presented to show the effectiveness of proposed approach in improving the robot performance (tracking accuracy) while still guaranteeing an interaction-friendly behavior when contact occurs.
Navvab Kashiri, Matteo Laffranchi, Nikolaos G. Tsagarakis, Alessio Margan, Darwin G. Caldwell
ICRA4