02581nas a2200181 4500008004100000245009500041210006900136260001200205300000900217520181500226653001302041100001802054700001602072700001902088700001702107700001502124856026002139 2017 eng d00aOn the Minimum-Time Control Problem for Differential Drive Robots with Bearing Constraints0 aMinimumTime Control Problem for Differential Drive Robots with B c04/2017 a1-273 a

This paper presents a study of analysis of minimum-time trajectories for a differential drive robot equipped with a fixed and limited field-of-view camera, which must keep a given landmark in view during maneuvers. Previous works have considered the same physical problem and provided a complete analysis/synthesis for the problem of determining the shortest paths. The main difference in the two cost functions (length vs. time) lays on the rotation on the spot. Indeed, this maneuver has zero cost in terms of length and hence leads to a 2D shortest path synthesis. On the other hand, in case of minimum time, the synthesis depends also on the orientations of the vehicle. In other words, the not zero cost of the rotation on the spot maneuvers leads to a 3D minimum-time synthesis. Moreover, the shortest paths have been obtained by exploiting the geometric properties of the extremal arcs, i.e., straight lines, rotations on the spot, logarithmic spirals and involute of circles. Conversely, in terms of time, even if the extremal arcs of the minimum-time control problem are exactly the same, the geometric properties of these arcs change, leading to a completely different analysis and characterization of optimal paths. In this paper, after proving the existence of optimal trajectories and showing the extremal arcs of the problem at hand, we provide the control laws that steer the vehicle along these arcs and the time-cost along each of them. Moreover, this being a crucial step toward numerical implementation, optimal trajectories are proved to be characterized by a finite number of switching points between different extremal arcs, i.e., the concatenations of extremal arcs with infinitely many junction times are shown to violate the optimality conditions.

10aRobotics1 aCristofaro, A1 aSalaris, P.1 aPallottino, L.1 aGiannoni, F.1 aBicchi, A. uhttp://download.springer.com/static/pdf/641/art%253A10.1007%252Fs10957-017-1110-7.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs10957-017-1110-7&token2=exp=1492507070~acl=%2Fstatic%2Fpdf%2F641%2Fart%25253A10.1007%25252Fs10957-017-11101788nas 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 a

Several 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.

10aRobotics1 aSettimi, A1 aCaporale, D.1 aKryczka, P.1 aFerrati, M.1 aPallottino, L. uhttp://ieeexplore.ieee.org/document/7803402/01790nas a2200181 4500008003900000245005400039210005400093260005000147300001600197520124300213653001301456100001601469700001401485700001501499700001401514700001901528856006101547 2016 d00aMulti–object handling for robotic manufacturing0 aMulti–object handling for robotic manufacturing aFlorence, Italy, October 24-27bIEEEc12/2016 a6887 - 68933 a

The purpose of this work is to move a step toward the automation of industrial plants through full exploitation of autonomous robots. A planning algorithm is proposed to move different objects in desired configurations with heterogeneous robots such as manipulators, mobile robots and conveyor belts.
The proposed approach allows different objects to be handled by different robots simultaneously in an efficient way and avoiding collisions with the environment and self–collisions between robots. In particular, the integrated system will be capable of planning paths for a set of objects from various starting points in the environment (e.g. shelves) to their respective final destinations. The proposed approach unifies the active (e.g., grasping by a hand) and passive (e.g., holding by a table) steps involved in moving the objects in the environment by treating them as end–effectors with constraints and capabilities.
Time varying graphs will be introduced to model the problem for simultaneous handling of objects by different end–effectors.
Optimal exploration of such graphs will be used to determine paths for each object with time constraints. Results will be validated through simulations.

10aRobotics1 aFerrati, M.1 aMarino, H1 aSettimi, A1 aNardi, S.1 aPallottino, L. uhttp://ieeexplore.ieee.org/document/7793936/?reload=true00614nas a2200169 4500008004100000245007100041210006900112260004900181300001700230653001300247100001400260700001700274700001800291700001500309700001900324856010100343 2012 eng d00aMotion Planning for Two 3D-Dubins Vehicles with Distance Contraint0 aMotion Planning for Two 3DDubins Vehicles with Distance Contrain aVilamoura, Algarve, PortugalcOctober 7 - 12 a4702 - 4707 10aRobotics1 aMarino, H1 aBonizzato, M1 aBartalucci, R1 aSalaris, P1 aPallottino, L. uhttp://95.110.227.16/publications/motion-planning-two-3d-dubins-vehicles-distance-contraint.html00508nas a2200157 4500008004100000024001900041245005400060210005400114300001600168653002100184653001300205100001200218700001900230700001500249856008600264 2010 eng d ap. 2263 - 226900aMotion planning for Formations of Dubins Vehicles0 aMotion planning for Formations of Dubins Vehicles a2263 - 226910aEmbedded Control10aRobotics1 aWang, H1 aPallottino, L.1 aBicchi, A. uhttp://95.110.227.16/publications/motion-planning-formations-dubins-vehicles.html01411nas a2200169 4500008004100000245004900041210004900090300001400139520089700153653002101050653001301071100001601084700001901100700001901119700001501138856008801153 2004 eng d00aMotion Planning through Symbols and Lattices0 aMotion Planning through Symbols and Lattices a3914-39193 a

In this paper we propose a new approach to motion planning, based on the introduction of a lattice structure in the workspace of the robot, leading to efficient computations of plans for rather complex vehicles, and allowing for the implementation of optimization procedures in a rather straightforward way. The basic idea is the purposeful restriction of the set of possible inputfunctions to the vehicle to a finite set of symbols, or {\em control quanta},which, under suitable conditions, generate a regular lattice of reachable points. Once the lattice is generated and a convenient description computed, standard techniques in integer linear programming can be used to find a plan very efficiently. We also provide a correct and complete algorithm to the problem of finding an optimized plan (with respect e.g. to length minimization) consisting in a sequence of graph searches.

10aEmbedded Control10aRobotics1 aPancanti, S1 aPallottino, L.1 aSalvadorini, D1 aBicchi, A. uhttp://95.110.227.16/publications/motion-planning-through-symbols-and-lattices.html01067nas a2200157 4500008004100000245006300041210006300104520051000167653003500677653002400712653002800736100001900764700001300783700001500796856009800811 2001 eng d00aMixed Integer Programming for Aircraft Conflict Resolution0 aMixed Integer Programming for Aircraft Conflict Resolution3 a

This paper considers the problem of solving conflicts between several aircraft. Considering the case when only aircraft heading changes are allowed, we propose a formulation of the multi-aircraft conflict avoidance problem as a mixed-integer linear program, whose solution may be obtained within seconds with standard optimization software. While such a problem formulation and solution is still unsuitable for operational implementation, it may be used as part of a real or fast-time simulation.

10aAir Traffic Management Systems10aAutonomous Vehicles10aNavigation and Planning1 aPallottino, L.1 aFeron, E1 aBicchi, A. uhttp://95.110.227.16/publications/mixed-integer-programming-aircraft-conflict-resolution.html