Francesco Pierri

Dr. Francesco Pierri

orcid

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 August 2018 in IEEE Robotics & Automation Magazine
Verified
Journal Article
Open access
AOAnibal Ollero
Anibal Ollero
JCJuan Cortés
Juan Cortés
ASAngel Santamaria-Navarro
Angel Santamaria-Navarro
MSMiguel Angel Trujillo Soto
Miguel Angel Trujillo Soto
RBRibin Balachandran
Ribin Balachandran
FPFrancesco Pierri
Francesco Pierri

8 January 2015 in IEEE Transactions on Control Systems Technology
Verified
Journal Article
Closed access
FAFilippo Arrichiello
Filippo Arrichiello
AMAlessandro Marino
Alessandro Marino
FPFrancesco Pierri
Francesco Pierri
In this paper, we present a distributed fault detection and isolation (FDI) strategy for a team of networked robots that builds on a distributed controller-observer schema. Remarkably different from other works in literature, the proposed FDI approach makes each robot of the team able to detect and isolate faults occurring on other robots, even if they are not direct neighbors. By means of a local observer, each robot can estimate the overall state of the team and it can use such an estimate to compute its local control input to achieve global tasks. The same information used by the local observers is also used to compute residual vectors, whose aim is to allow the detection and the isolation of actuator faults occurring on any robot of the team. Adaptive thresholds are derived based on the dynamics of the residual vectors by considering the presence of nonzero initial observer estimation errors, and noise terms affecting state measurement and model dynamics. The approach is validated via both numerical simulations and experiments involving four Khepera III mobile robots.

8 July 2016 in Autonomous Robots
Verified
Journal Article
Open access
PDF file
KBK. Baizid
K. Baizid
GGG. Giglio
G. Giglio
FPFrancesco Pierri
Francesco Pierri
MSMiguel Angel Trujillo Soto
Miguel Angel Trujillo Soto
GAG. Antonelli
G. Antonelli
AOAnibal Ollero
Anibal Ollero
In this paper a behavioral control framework is developed to control an unmanned aerial vehicle-manipulator (UAVM) system, composed by a multirotor aerial vehicle equipped with a robotic arm. The goal is to ensure vehicle-arm coordination and manage complex multi-task missions, where different behaviors must be encompassed in a clear and meaningful way. In detail, a control scheme, based on the null space-based behavioral paradigm, is proposed to handle the coordination between the arm and vehicle motion. To this aim, a set of basic functionalities (elementary behaviors) are designed and combined in a given priority order, in order to attain more complex tasks (compound behaviors). A supervisor is in charge of switching between the compound behaviors according to the mission needs and the sensory feedback. The method is validated on a real testbed, consisting of a multirotor aircraft with an attached 6 Degree of Freedoms manipulator, developed within the EU-funded project ARCAS (Aerial Robotics Cooperative Assembly System). At the the best of authors’ knowledge, this is the first time that an UAVM system is experimentally tested in the execution of complex multi-task missions. The results show that, by properly designing a set of compound behaviors and a supervisor, vehicle-arm coordination in complex missions can be effectively managed.

1 June 2013
Verified
Conference Paper
Closed access
GAG. Arleo
G. Arleo
FCF. Caccavale
F. Caccavale
GMG. Muscio
G. Muscio
FPFrancesco Pierri
Francesco Pierri
In this paper a novel hierarchical motion control scheme for quadrotor aerial vehicles equipped with a manipulator is proposed. The controller is organized into two layers: in the top layer, an inverse kinematics algorithm computes the motion references for the actuated variables; in the bottom layer, a motion control algorithm is in charge of tracking the motion references computed by the top layer. A simulation case study is developed to demonstrate the effectiveness of the approach in the presence of disturbances and unmodeled dynamics.

31 January 2009 in Control Engineering Practice
Verified
Journal Article
Closed access
FCF. Caccavale
F. Caccavale
PCP. Cilibrizzi
P. Cilibrizzi
FPFrancesco Pierri
Francesco Pierri
Luigi VillaniLuigi Villani
Luigi Villani

29 June 2017 in IEEE Transactions on Control Systems Technology
Verified
Journal Article
Open access
GMG. Muscio
G. Muscio
FPFrancesco Pierri
Francesco Pierri
MTM. A. Trujillo
M. A. Trujillo
ECE. Cataldi
E. Cataldi
GAG. Antonelli
G. Antonelli
AOAnibal Ollero
Anibal Ollero
This brief presents a three-layer control architecture for coordinated control of multiple unmanned aerial vehicle manipulators (UAVMs): the centralized top layer plans the end-effector desired trajectories of each UAVM; the middle layer, local to each vehicle, computes the corresponding motion references; the bottom layer is a low level dynamic motion controller, which tracks the motion references. At second layer, the overall mission is hierarchically decomposed in a set of elementary behaviors, which are combined together, via the null space-based behavioral approach, into more complex compound behaviors. For each UAVM, the suitable compound behavior to be executed is selected by a supervisor. The proposed framework has been tested through an experimental campaign.