Perception-motivated parallel algorithms for haptics

Negli ultimi anni l\u2019utilizzo di dispositivi aptici, atti cio\ue8 a riprodurre l\u2019interazione fisica con l\u2019ambiente remoto o virtuale, si sta diffondendo in vari ambiti della robotica e dell\u2019informatica, dai videogiochi alla chirurgia robotizzata eseguita in teleoperazione, dai cellulari alla riabilitazione. In questo lavoro di tesi abbiamo voluto considerare nuovi punti di vista sull\u2019argomento, allo scopo di comprendere meglio come riportare l\u2019essere umano, che \ue8 l\u2019unico fruitore del ritorno di forza, tattile e di telepresenza, al centro della ricerca sui dispositivi aptici. Allo scopo ci siamo focalizzati su due aspetti: una manipolazione del segnale di forza mutuata dalla percezione umana e l\u2019utilizzo di architetture multicore per l\u2019implementazione di algoritmi aptici e robotici. Con l\u2019aiuto di un setup sperimentale creato ad hoc e attraverso l\u2019utilizzo di un joystick con ritorno di forza a 6 gradi di libert\ue0, abbiamo progettato degli esperimenti psicofisici atti all\u2019identificazione di soglie differenziali di forze/coppie nel sistema mano-braccio. Sulla base dei risultati ottenuti abbiamo determinato una serie di funzioni di scalatura del segnale di forza, una per ogni grado di libert\ue0, che permettono di aumentare l\u2019abilit\ue0 umana nel discriminare stimoli differenti. L\u2019utilizzo di tali funzioni, ad esempio in teleoperazione, richiede la possibilit\ue0 di variare il segnale di feedback e il controllo del dispositivo sia in relazione al lavoro da svolgere, sia alle peculiari capacit\ue0 dell\u2019utilizzatore. La gestione del dispositivo deve quindi essere in grado di soddisfare due obbiettivi tendenzialmente in contrasto, e cio\ue8 il raggiungimento di alte prestazioni in termini di velocit\ue0, stabilit\ue0 e precisione, abbinato alla flessibilit\ue0 tipica del software. Una soluzione consiste nell\u2019affidare il controllo del dispositivo ai nuovi sistemi multicore che si stanno sempre pi\uf9 prepotentemente affacciando sul panorama informatico. Per far ci\uf2 una serie di algoritmi consolidati deve essere portata su sistemi paralleli. In questo lavoro abbiamo dimostrato che \ue8 possibile convertire facilmente vecchi algoritmi gi\ue0 implementati in hardware, e quindi intrinsecamente paralleli. Un punto da definire rimane per\uf2 quanto costa portare degli algoritmi solitamente descritti in VLSI e schemi in un linguaggio di programmazione ad alto livello. Focalizzando la nostra attenzione su un problema specifico, la pseudoinversione di matrici che \ue8 presente in molti algoritmi di dinamica e cinematica, abbiamo mostrato che un\u2019attenta progettazione e decomposizione del problema permette una mappatura diretta sulle unit\ue0 di calcolo disponibili. In aggiunta, l\u2019uso di parallelismo a livello di dati su macchine SIMD permette di ottenere buone prestazioni utilizzando semplici operazioni vettoriali come addizioni e shift. Dato che di solito tali istruzioni fanno parte delle implementazioni hardware la migrazione del codice risulta agevole. Abbiamo testato il nostro approccio su una Sony PlayStation 3 equipaggiata con un processore IBM Cell Broadband Engine.In the last years the use of haptic feedback has been used in several applications, from mobile phones to rehabilitation, from video games to robotic aided surgery. The haptic devices, that are the interfaces that create the stimulation and reproduce the physical interaction with virtual or remote environments, have been studied, analyzed and developed in many ways. Every innovation in the mechanics, electronics and technical design of the device it is valuable, however it is important to maintain the focus of the haptic interaction on the human being, who is the only user of force feedback. In this thesis we worked on two main topics that are relevant to this aim: a perception based force signal manipulation and the use of modern multicore architectures for the implementation of the haptic controller. With the help of a specific experimental setup and using a 6 dof haptic device we designed a psychophysical experiment aimed at identifying of the force/torque differential thresholds applied to the hand-arm system. On the basis of the results obtained we determined a set of task dependent scaling functions, one for each degree of freedom of the three-dimensional space, that can be used to enhance the human abilities in discriminating different stimuli. The perception based manipulation of the force feedback requires a fast, stable and configurable controller of the haptic interface. Thus a solution is to use new available multicore architectures for the implementation of the controller, but many consolidated algorithms have to be ported to these parallel systems. Focusing on specific problem, i.e. the matrix pseudoinversion, that is part of the robotics dynamic and kinematic computation, we showed that it is possible to migrate code that was already implemented in hardware, and in particular old algorithms that were inherently parallel and thus not competitive on sequential processors. The main question that still lies open is how much effort is required in order to write these algorithms, usually described in VLSI or schematics, in a modern programming language. We show that a careful task decomposition and design permit a mapping of the code on the available cores. In addition, the use of data parallelism on SIMD machines can give good performance when simple vector instructions such as add and shift operations are used. Since these instructions are present also in hardware implementations the migration can be easily performed. We tested our approach on a Sony PlayStation 3 game console equipped with IBM Cell Broadband Engine processor

Parallel Multiscale Contact Dynamics for Rigid Non-spherical Bodies

The simulation of large numbers of rigid bodies of non-analytical shapes or vastly varying sizes which collide with each other is computationally challenging. The fundamental problem is the identification of all contact points between all particles at every time step. In the Discrete Element Method (DEM), this is particularly difficult for particles of arbitrary geometry that exhibit sharp features (e.g. rock granulates). While most codes avoid non-spherical or non-analytical shapes due to the computational complexity, we introduce an iterative-based contact detection method for triangulated geometries. The new method is an improvement over a naive brute force approach which checks all possible geometric constellations of contact and thus exhibits a lot of execution branching. Our iterative approach has limited branching and high floating point operations per processed byte. It thus is suitable for modern Single Instruction Multiple Data (SIMD) CPU hardware. As only the naive brute force approach is robust and always yields a correct solution, we propose a hybrid solution that combines the best of the two worlds to produce fast and robust contacts. In terms of the DEM workflow, we furthermore propose a multilevel tree-based data structure strategy that holds all particles in the domain on multiple scales in grids. Grids reduce the total computational complexity of the simulation. The data structure is combined with the DEM phases to form a single touch tree-based traversal that identifies both contact points between particle pairs and introduces concurrency to the system during particle comparisons in one multiscale grid sweep. Finally, a reluctant adaptivity variant is introduced which enables us to realise an improved time stepping scheme with larger time steps than standard adaptivity while we still minimise the grid administration overhead. Four different parallelisation strategies that exploit multicore architectures are discussed for the triad of methodological ingredients. Each parallelisation scheme exhibits unique behaviour depending on the grid and particle geometry at hand. The fusion of them into a task-based parallelisation workflow yields promising speedups. Our work shows that new computer architecture can push the boundary of DEM computability but this is only possible if the right data structures and algorithms are chosen