00479nas a2200133 4500008004100000245011200041210006900153300001400222490000700236100001700243700001700260700001900277856004900296 2021 eng d00aOn Null Space-Based Inverse Kinematics Techniques for Fleet Management: Toward Time-Varying Task Activation0 aNull SpaceBased Inverse Kinematics Techniques for Fleet Manageme a257 - 2740 v371 aMannucci, A.1 aCaporale, D.1 aPallottino, L. uhttps://ieeexplore.ieee.org/document/919432100462nas a2200145 4500008004100000245006800041210006700109490000700176100001400183700001700197700001500214700001900229700001700248856005100265 2020 eng d00aLiDAR-Based GNSS Denied Localization for Autonomous Racing Cars0 aLiDARBased GNSS Denied Localization for Autonomous Racing Cars0 v201 aMassa, F.1 aBonamini, L.1 aSettimi, A1 aPallottino, L.1 aCaporale, D. uhttps://www.mdpi.com/1424-8220/20/14/3992#cite00544nas a2200145 4500008004100000245007400041210006900115100001500184700001800199700001700217700001700234700001700251700001500268856011500283 2019 eng d00aAnalysis of series elasticity in locomotion of a planar bipedal robot0 aAnalysis of series elasticity in locomotion of a planar bipedal 1 aManara, S.1 aGasparri, G M1 aGarabini, M.1 aCaporale, D.1 aGabiccini, M1 aBicchi, A. uhttp://www.centropiaggio.unipi.it/publications/analysis-series-elasticity-locomotion-planar-bipedal-robot.html00642nas a2200181 4500008004100000245008200041210006900123100001700192700001500209700001400224700001700238700001400255700001700269700001700286700001500303700001900318856012300337 2019 eng d00aTowards the Design of Robotic Drivers for Full-Scale Self-Driving Racing Cars0 aTowards the Design of Robotic Drivers for FullScale SelfDriving 1 aCaporale, D.1 aSettimi, A1 aMassa, F.1 aAmerotti, F.1 aCorti, A.1 aFagiolini, A1 aGuiggiani, M1 aBicchi, A.1 aPallottino, L. uhttp://www.centropiaggio.unipi.it/publications/towards-design-robotic-drivers-full-scale-self-driving-racing-cars.html01821nas a2200241 4500008004100000245015800041210006900199300001600268490000600284520098400290100001801274700001501292700001701307700001501324700001501339700001401354700002001368700001501388700001601403700001501419700001701434856012801451 2018 eng d00aEfficient Walking Gait Generation via Principal Component Representation of Optimal Trajectories: Application to a Planar Biped Robot With Elastic Joints0 aEfficient Walking Gait Generation via Principal Component Repres a2299–23060 v33 a
Recently, the method of choice to exploit robot dynamics for efficient walking is numerical optimization (NO). The main drawback in NO is the computational complexity, which strongly affects the time demand of the solution. Several strategies can be used to make the optimization more treatable and to efficiently describe the solution set. In this letter, we present an algorithm to encode effective walking references, generated offline via numerical optimization, extracting a limited number of principal components and using them as a basis of optimal motions. By combining these components, a good approximation of the optimal gaits can be generated at run time. The advantages of the presented approach are discussed, and an extensive experimental validation is carried out on a planar legged robot with elastic joints. The biped thus controlled is able to start and stop walking on a treadmill, and to control its speed dynamically as the treadmill speed changes.
1 aGasparri, G M1 aManara, S.1 aCaporale, D.1 aAverta, G.1 aBonilla, M1 aMarino, H1 aCatalano, M. G.1 aGrioli, G.1 aBianchi, M.1 aBicchi, A.1 aGarabini, M. uhttp://www.centropiaggio.unipi.it/publications/efficient-walking-gait-generation-principal-component-representation-optimal01088nas a2200373 4500008004100000022001400041245007100055210006900126300000800195653001400203653001600217653001300233653002200246653002600268653001800294100001700312700001500329700001700344700001600361700001700377700001700394700001700411700001600428700001700444700001900461700001500480700001900495700002000514700001800534700001500552700001700567700002000584856011000604 2018 eng d a1070-993200aHumanoids at Work: The WALK-MAN Robot in a Postearthquake Scenario0 aHumanoids at Work The WALKMAN Robot in a Postearthquake Scenario a1-110aBuildings10aEarthquakes10aHardware10aLegged locomotion10aRobot sensing systems10aTask analysis1 aNegrello, F.1 aSettimi, A1 aCaporale, D.1 aLentini, G.1 aPoggiani, M.1 aKanoulas, D.1 aMuratore, L.1 aLuberto, E.1 aSantaera, G.1 aCiarleglio, L.1 aErmini, L.1 aPallottino, L.1 aCaldwell, D. G.1 aTsagarakis, N1 aBicchi, A.1 aGarabini, M.1 aCatalano, M. G. uhttp://www.centropiaggio.unipi.it/publications/humanoids-work-walk-man-robot-postearthquake-scenario.html00696nas a2200217 4500008003900000245006700039210006400106260002500170300000800195100001700203700001700220700001900237700001500256700001500271700001700286700001400303700001600317700001400333700001800347856011300365 2018 d00aA Planning and Control System for Self-Driving Racing Vehicles0 aPlanning and Control System for SelfDriving Racing Vehicles aPalermo, ItalycSept a1-61 aCaporale, D.1 aFagiolini, A1 aPallottino, L.1 aSettimi, A1 aBiondo, A.1 aAmerotti, F.1 aMassa, F.1 aDe Caro, S.1 aCorti, A.1 aVenturini, L. uhttp://www.centropiaggio.unipi.it/publications/planning-and-control-system-self-driving-racing-vehicles.html01788nas a2200193 4500008003900000245011800039210006900157260004400226300001400270490006900284520107100353653002101424653001301445100001901458700001701477700001501494700001901509856006601528 2016 d00aAPRICOT: Aerospace PRototypIng COntrol Toolbox. A Modeling and Simulation Environment for Aircraft Control Design0 aAPRICOT Aerospace PRototypIng COntrol Toolbox A Modeling and Sim aRome, Italy, June 15-16, 2016bSpringer a139 - 1570 v9991 of the book series Lecture Notes in Computer Science (LNCS)3 aA novel MATLAB/Simulink based modeling and simulation environment for the design and rapid prototyping of state-of-the-art aircraft control systems is proposed. The toolbox, named APRICOT, is able to simulate the longitudinal and laterodirectional dynamics of an aircraft separately, as well as the complete 6 degrees of freedom dynamics. All details of the dynamics can be easily customized in the toolbox, some examples are shown in the paper. Moreover, different aircraft models can be easily integrated. The main goal of APRICOT is to provide a simulation environment to test and validate different control laws with different aircraft models. Hence, the proposed toolbox has applicability both for educational purposes and control rapid prototyping. With respect to similar software packages, APRICOT is customizable in all its aspects, and has been released as open source software. An interface with Flightgear Simulator allows for online visualization of the flight. Examples of control design with simulation experiments are reported and commented.
10aEmbedded Control10aRobotics1 aFerrarelli, A.1 aCaporale, D.1 aSettimi, A1 aPallottino, L. uhttp://link.springer.com/chapter/10.1007/978-3-319-47605-6_1101788nas a2200181 4500008003900000020002300039245007300062210007100135260004300206520121200249653001301461100001501474700001701489700001601506700001601522700001901538856004901557 2016 d a978-1-5090-4718-5 00aMotion Primitive Based Random Planning for Loco–Manipulation Tasks0 aMotion Primitive Based Random Planning for Loco–Manipulation Tas aCancun, Mexico, 15-17 Nov. 2016 bIEEE3 aSeveral advanced control laws are available for
complex robotic systems such as humanoid robots and mobile
manipulators. Controls are usually developed for locomotion or
for manipulation purposes. Resulting motions are usually executed
sequentially and the potentiality of the robotic platform
is not fully exploited.
In this work we consider the problem of loco–manipulation
planning for a robot with given parametrized control laws
known as primitives. Such primitives, may have not been
designed to be executed simultaneously and by composing
them instability may easily arise. With the proposed approach,
primitives combination that guarantee stability of the system
are obtained resulting in complex whole–body behavior.
A formal definition of motion primitives is provided and a
random sampling approach on a manifold with limited dimension
is investigated. Probabilistic completeness and asymptotic
optimality are also proved. The proposed approach is tested
both on a mobile manipulator and on the humanoid robot
Walk-Man, performing loco–manipulation tasks.