Model learning for trajectory tracking of robot manipulators

Abstract Model based controllers have drastically improved robot performance, increasing task accuracy while reducing control effort. Nevertheless, all this was realized with a very strong assumption: the exact knowledge of the physical properties of both the robot and the environment that surrounds it. This assertion is often misleading: in fact modern robots are modeled in a very approximate way and, more important, the environment is almost never static and completely known. Also for systems very simple, such as robot manipulators, these assumptions are still too strong and must be relaxed. Many methods were developed which, exploiting previous experiences, are able to refine the nominal model: from classic identification techniques to more modern machine learning based approaches. Indeed, the topic of this thesis is the investigation of these data driven techniques in the context of robot control for trajectory tracking. In the first two chapters, preliminary knowledge is provided on both model based controllers, used in robotics to assure precise trajectory tracking, and model learning techniques. In the following three chapters, are presented the novelties introduced by the author in this context with respect to the state of the art: three works with the same premise (an inaccurate system modeling), an identical goal (accurate trajectory tracking control) but with small differences according to the specific platform of application (fully actuated, underactuated, redundant robots). In all the considered architectures, an online learning scheme has been introduced to correct the nominal feedback linearization control law. Indeed, the method has been primarily introduced in the literature to cope with fully actuated systems, showing its efficacy in the accurate tracking of joint space trajectories also with an inaccurate dynamic model. The main novelty of the technique was the use of only kinematics information, instead of torque measurements (in general very noisy), to online retrieve and compensate the dynamic mismatches. After that the method has been extended to underactuated robots. This new architecture was composed by an online learning correction of the controller, acting on the actuated part of the system (the nominal partial feedback linearization), and an offline planning phase, required to realize a dynamically feasible trajectory also for the zero dynamics of the system. The scheme was iterative: after each trial, according to the collected information, both the phases were improved and then repeated until the task achievement. Also in this case the method showed its capability, both in numerical simulations and on real experiments on a robotics platform. Eventually the method has been applied to redundant systems: differently from before, in this context the task consisted in the accurate tracking of a Cartesian end effector trajectory. In principle very similar to the fully actuated case, the presence of redundancy slowed down drastically the learning machinery convergence, worsening the performance. In order to cope with this, a redundancy resolution was proposed that, exploiting an approximation of the learning algorithm (Gaussian process regression), allowed to locally maximize the information and so select the most convenient self motion for the system; moreover, all of this was realized with just the resolution of a quadratic programming problem. Also in this case the method showed its performance, realizing an accurate online tracking while reducing both the control effort and the joints velocity, obtaining so a natural behaviour. The thesis concludes with summary considerations on the proposed approach and with possible future directions of research

Exploiting Robot Redundancy for Online Learning and Control

Accurate trajectory tracking in the task space is critical in many robotics applications. Model-based robot controllers are able to ensure very good tracking but lose effectiveness in the presence of model uncertainties. On the other hand, online learning-based control laws can handle poor dynamic modeling, as long as prediction errors are kept small and decrease over time. However, in the case of redundant robots directly controlled in the task space, this condition is not usually met. We present an online learning-based control framework that exploits robot redundancy so as to increase the overall performance and shorten the learning transient. The validity of the proposed approach is shown through a comparative study conducted in simulation on a KUKA LWR4+ robot

Linear or Nonlinear Modeling for ENSO Dynamics?

The observed ENSO statistics exhibits a non-Gaussian behavior, which is indicative of the presence of nonlinear processes. In this paper, we use the Recharge Oscillator Model (ROM), a largely used Low-Order Model (LOM) of ENSO, as well as methodologies borrowed from the field of statistical mechanics to identify which aspects of the system may give rise to nonlinearities that are consistent with the observed ENSO statistics. In particular, we are interested in understanding whether the nonlinearities reside in the system dynamics or in the fast atmospheric forcing. Our results indicate that one important dynamical nonlinearity often introduced in the ROM cannot justify a non-Gaussian system behavior, while the nonlinearity in the atmospheric forcing can instead produce a statistics similar to the observed. The implications of the non-Gaussian character of ENSO statistics for the frequency of extreme El Nino events is then examined

Coral Patch and Ormonde seamounts as a product of the Madeira hotspot, Eastern Atlantic Ocean

New detailed swath bathymetry and bottom samples from Coral Patch and Ormonde seamounts provide constraints on the emplacement of the Madeira hotspot in the Eastern Atlantic Ocean. Swath bathymetric data document that Coral Patch is a composite structure, made up of at least nine distinct volcanic centres. Lithified pelagic carbonates infilling fissures in lava blocks constrain a minimal age for the volcanism in the Early Miocene and represent the first documentation of Coral Patch acting as an offshore terrigenous-starved seamount. At Coral Patch, as already observed at the Ormonde seamount, volcanism was emplaced on top of a pre-existing relief resulting from the regional tectonic compressive regime

AC/DC: The FERMI FEL Split and Delay Optical Device for Ultrafast X-ray Science

Free-electron lasers (FELs) are the most advanced class of light-sources, by virtue of their unique capability to lase high-brightness pulses characterized by wavelengths spanning the extreme-ultraviolet, the soft and hard X-ray spectral domains, as well as by temporal lengths lying in the femtosecond (fs) timescale. The next step to push the current standards in ultrafast X-ray science is strongly linked to the possibility of engineering and exploiting time-resolved experiments exclusively for FELs pulses, ideally having different colors tunable at specific electronic resonance of the chemical elements. At the seeded FERMI FEL (Trieste, Italy) this goal is committed to the optical device known as AC/DC, which stands for the auto correlator/delay creator. AC/DC is designed to double the incoming FEL pulse splitting the photon beam by inserting a grazing incidence flat mirror, thus preserving the spectral and temporal properties, and further delaying one of these two pulses in time. It can independently tune the FEL pulses fluence on the two optical paths by means of solid-state filters, too. Here, we present a detailed description about this optical device. Strong emphasis is dedicated to the AC/DC opto-mechanical design and to the laser-based feedback systems implemented to compensate for any mismatch affecting the FEL optical trajectory, ascribable to both mechanical imperfections and paraxial errors rising during a temporal delay scan

Widely tunable two-colour seeded free-electron laser source for resonant-pump resonant-probe magnetic scattering

International audienceThe advent of free-electron laser (FEL) sources delivering two synchronized pulses of different wavelengths (or colours) has made available a whole range of novel pump–probe experiments. This communication describes a major step forward using a new configuration of the FERMI FEL-seeded source to deliver two pulses with different wavelengths, each tunable independently over a broad spectral range with adjustable time delay. The FEL scheme makes use of two seed laser beams of different wavelengths and of a split radiator section to generate two extreme ultraviolet pulses from distinct portions of the same electron bunch. The tunability range of this new two-colour source meets the requirements of double-resonant FEL pump/FEL probe time-resolved studies. We demonstrate its performance in a proof-of-principle magnetic scattering experiment in Fe–Ni compounds, by tuning the FEL wavelengths to the Fe and Ni 3p resonances

FEL stochastic spectroscopy revealing silicon bond softening dynamics

Time-resolved X-ray Emission/Absorption Spectroscopy (Tr-XES/XAS) is an informative experimental tool sensitive to electronic dynamics in materials, widely exploited in diverse research fields. Typically, Tr-XES/XAS requires X-ray pulses with both a narrow bandwidth and sub-picosecond pulse duration, a combination that in principle finds its optimum with Fourier transform-limited pulses. In this work, we explore an alternative xperimental approach, capable of simultaneously retrieving information about unoccupied (XAS) and occupied (XES) states from the stochastic fluctuations of broadband extreme ultraviolet pulses of a free-electron laser. We used this method, in combination with singular value decomposition and Tikhonov regularization procedures, to determine the XAS/XES response from a crystalline silicon sample at the L2,3-edge, with an energy resolution of a few tens of meV. Finally, we combined this spectroscopic method with a pump-probe approach to measure structural and electronic dynamics of a silicon membrane. Tr-XAS/XES data obtained after photoexcitation with an optical laser pulse at 390 nm allowed us to observe perturbations of the band structure, which are compatible with the formation of the predicted precursor state of a non-thermal solid-liquid phase transition associated with a bond softening phenomenon

Timing methodologies and studies at the FERMI free-electron laser.

Time-resolved investigations have begun a new era of chemistry and physics, enabling the monitoring in real time of the dynamics of chemical reactions and matter. Induced transient optical absorption is a basic ultrafast electronic effect, originated by a partial depletion of the valence band, that can be triggered by exposing insulators and semiconductors to sub-picosecond extreme-ultraviolet pulses. Besides its scientific and fundamental implications, this process is very important as it is routinely applied in free-electron laser (FEL) facilities to achieve the temporal superposition between FEL and optical laser pulses with tens of femtoseconds accuracy. Here, a set of methodologies developed at the FERMI facility based on ultrafast effects in condensed materials and employed to effectively determine the FEL/laser cross correlation are presented