Reconfigurable Computing Systems for Robotics using a Component-Oriented Approach

Robotic platforms are becoming more complex due to the wide range of modern applications, including multiple heterogeneous sensors and actuators. In order to comply with real-time and power-consumption constraints, these systems need to process a large amount of heterogeneous data from multiple sensors and take action (via actuators), which represents a problem as the resources of these systems have limitations in memory storage, bandwidth, and computational power. Field Programmable Gate Arrays (FPGAs) are programmable logic devices that offer high-speed parallel processing. FPGAs are particularly well-suited for applications that require real-time processing, high bandwidth, and low latency. One of the fundamental advantages of FPGAs is their flexibility in designing hardware tailored to specific needs, making them adaptable to a wide range of applications. They can be programmed to pre-process data close to sensors, which reduces the amount of data that needs to be transferred to other computing resources, improving overall system efficiency. Additionally, the reprogrammability of FPGAs enables them to be repurposed for different applications, providing a cost-effective solution that needs to adapt quickly to changing demands. FPGAs' performance per watt is close to that of Application-Specific Integrated Circuits (ASICs), with the added advantage of being reprogrammable. Despite all the advantages of FPGAs (e.g., energy efficiency, computing capabilities), the robotics community has not fully included them so far as part of their systems for several reasons. First, designing FPGA-based solutions requires hardware knowledge and longer development times as their programmability is more challenging than Central Processing Units (CPUs) or Graphics Processing Units (GPUs). Second, porting a robotics application (or parts of it) from software to an accelerator requires adequate interfaces between software and FPGAs. Third, the robotics workflow is already complex on its own, combining several fields such as mechanics, electronics, and software. There have been partial contributions in the state-of-the-art for FPGAs as part of robotics systems. However, a study of FPGAs as a whole for robotics systems is missing in the literature, which is the primary goal of this dissertation. Three main objectives have been established to accomplish this. (1) Define all components required for an FPGAs-based system for robotics applications as a whole. (2) Establish how all the defined components are related. (3) With the help of Model-Driven Engineering (MDE) techniques, generate these components, deploy them, and integrate them into existing solutions. The component-oriented approach proposed in this dissertation provides a proper solution for designing and implementing FPGA-based designs for robotics applications. The modular architecture, the tool 'FPGA Interfaces for Robotics Middlewares' (FIRM), and the toolchain 'FPGA Architectures for Robotics' (FAR) provide a set of tools and a comprehensive design process that enables the development of complex FPGA-based designs more straightforwardly and efficiently. The component-oriented approach contributed to the state-of-the-art in FPGA-based designs significantly for robotics applications and helps to promote their wider adoption and use by specialists with little FPGA knowledge

Fundamentals

Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

Autonomous Operation of a Reconfigurable Multi-Robot System for Planetary Space Missions

Reconfigurable robots can physically merge and form new types of composite systems. This ability leads to additional degrees of freedom for robot operations especially when dynamically composed robotic systems offer capabilities that none of the individual systems have. Research in the area of reconfigurable multi-robot systems has mainly been focused on swarm-based robots and thereby to systems with a high degree of modularity but a heavily restricted set of capabilities. In contrast, this thesis deals with heterogeneous robot teams comprising individually capable robots which are also modular and reconfigurable. In particular, the autonomous application of such reconfigurable multi-robot systems to enhance robotic space exploration missions is investigated. Exploiting the flexibility of a reconfigurable multi-robot system requires an appropriate system model and reasoner. Hence, this thesis introduces a special organisation model. This model accounts for the key characteristics of reconfigurable robots which are constrained by the availability and compatibility of hardware interfaces. A newly introduced mapping function between resource structures and functional properties permits to characterise dynamically created agent compositions. Since a combinatorial challenge lies in the identification of feasible and functionally suitable agents, this thesis further suggests bounding strategies to reason efficiently with composite robotic systems. This thesis proposes a mission planning algorithm which permits to exploit the flexibility of reconfigurable multi-robot systems. The implemented planner builds upon the developed organisation model so that multi-robot missions can be specified by high-level functionality constraints which are resolved to suitable combinations of robots. Furthermore, the planner synchronises robot activities over time and characterises plans according to three objectives: efficacy, efficiency and safety. The plannera s evaluation demonstrates an optimization of an exemplary space mission. This research is based on the parallel development of theoretical concepts and practical solutions while working with three reconfigurable multi-robot teams. The operation of a reconfigurable robotic team comes with practical constraints. Therefore, this thesis composes and evaluates an operational infrastructure which can serve as reference implementation. The identification and combination of applicable state-of-the-art technologies result in a distributed and dynamically extensible communication infrastructure which can maintain the properties of reconfigurable multi-robot systems. Field tests covering semi-autonomous and autonomous operation have been performed to characterise multi-robot missions and validate the autonomous control approach for reconfigurable multi-robot systems. The practical evaluation identified critical constraints and design elements for a successful application of reconfigurable multi-robot systems. Furthermore, the experiments point to improvements for the organisation model. This thesis is a wholistic approach to automate reconfigurable multi-robot systems. It identifies theoretical as well as practical challenges and it suggests effective solutions which permit an exploitation of an increased level of flexibility in future robotics missions

Autonomous Operation of a Reconfigurable Multi-Robot System for Planetary Space Missions

Reconfigurable robots can physically merge and form new types of composite systems. This ability leads to additional degrees of freedom for robot operations especially when dynamically composed robotic systems offer capabilities that none of the individual systems have. Research in the area of reconfigurable multi-robot systems has mainly been focused on swarm-based robots and thereby to systems with a high degree of modularity but a heavily restricted set of capabilities. In contrast, this thesis deals with heterogeneous robot teams comprising individually capable robots which are also modular and reconfigurable. In particular, the autonomous application of such reconfigurable multi-robot systems to enhance robotic space exploration missions is investigated. Exploiting the flexibility of a reconfigurable multi-robot system requires an appropriate system model and reasoner. Hence, this thesis introduces a special organisation model. This model accounts for the key characteristics of reconfigurable robots which are constrained by the availability and compatibility of hardware interfaces. A newly introduced mapping function between resource structures and functional properties permits to characterise dynamically created agent compositions. Since a combinatorial challenge lies in the identification of feasible and functionally suitable agents, this thesis further suggests bounding strategies to reason efficiently with composite robotic systems. This thesis proposes a mission planning algorithm which permits to exploit the flexibility of reconfigurable multi-robot systems. The implemented planner builds upon the developed organisation model so that multi-robot missions can be specified by high-level functionality constraints which are resolved to suitable combinations of robots. Furthermore, the planner synchronises robot activities over time and characterises plans according to three objectives: efficacy, efficiency and safety. The plannera s evaluation demonstrates an optimization of an exemplary space mission. This research is based on the parallel development of theoretical concepts and practical solutions while working with three reconfigurable multi-robot teams. The operation of a reconfigurable robotic team comes with practical constraints. Therefore, this thesis composes and evaluates an operational infrastructure which can serve as reference implementation. The identification and combination of applicable state-of-the-art technologies result in a distributed and dynamically extensible communication infrastructure which can maintain the properties of reconfigurable multi-robot systems. Field tests covering semi-autonomous and autonomous operation have been performed to characterise multi-robot missions and validate the autonomous control approach for reconfigurable multi-robot systems. The practical evaluation identified critical constraints and design elements for a successful application of reconfigurable multi-robot systems. Furthermore, the experiments point to improvements for the organisation model. This thesis is a wholistic approach to automate reconfigurable multi-robot systems. It identifies theoretical as well as practical challenges and it suggests effective solutions which permit an exploitation of an increased level of flexibility in future robotics missions

Fundamentals

Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

Optimal Control Algorithms and Their Analysis for Short-Term Scheduling in Manufacturing Systems

International audienceCurrent literature presents optimal control computational algorithms with regard to state, control, and conjunctive variable spaces. This paper first analyses the advantages and limitations of different optimal control computational methods and algorithms which can be used for short-term scheduling. Second, it develops an optimal control computational algorithm that allows for the solution of short-term scheduling in an optimal manner. Moreover, qualitative and quantitative analysis of the manufacturing system scheduling problem is presented. Results highlight computer experiments with a scheduling software prototype as well as potential future research avenues

Dependable Embedded Systems

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems

Energy-Efficient and Reliable Computing in Dark Silicon Era

Dark silicon denotes the phenomenon that, due to thermal and power constraints, the fraction of transistors that can operate at full frequency is decreasing in each technology generation. Moore’s law and Dennard scaling had been backed and coupled appropriately for five decades to bring commensurate exponential performance via single core and later muti-core design. However, recalculating Dennard scaling for recent small technology sizes shows that current ongoing multi-core growth is demanding exponential thermal design power to achieve linear performance increase. This process hits a power wall where raises the amount of dark or dim silicon on future multi/many-core chips more and more. Furthermore, from another perspective, by increasing the number of transistors on the area of a single chip and susceptibility to internal defects alongside aging phenomena, which also is exacerbated by high chip thermal density, monitoring and managing the chip reliability before and after its activation is becoming a necessity. The proposed approaches and experimental investigations in this thesis focus on two main tracks: 1) power awareness and 2) reliability awareness in dark silicon era, where later these two tracks will combine together. In the first track, the main goal is to increase the level of returns in terms of main important features in chip design, such as performance and throughput, while maximum power limit is honored. In fact, we show that by managing the power while having dark silicon, all the traditional benefits that could be achieved by proceeding in Moore’s law can be also achieved in the dark silicon era, however, with a lower amount. Via the track of reliability awareness in dark silicon era, we show that dark silicon can be considered as an opportunity to be exploited for different instances of benefits, namely life-time increase and online testing. We discuss how dark silicon can be exploited to guarantee the system lifetime to be above a certain target value and, furthermore, how dark silicon can be exploited to apply low cost non-intrusive online testing on the cores. After the demonstration of power and reliability awareness while having dark silicon, two approaches will be discussed as the case study where the power and reliability awareness are combined together. The first approach demonstrates how chip reliability can be used as a supplementary metric for power-reliability management. While the second approach provides a trade-off between workload performance and system reliability by simultaneously honoring the given power budget and target reliability

Architecture FPGA améliorée et flot de conception pour une reconfiguration matérielle en ligne efficace

The self-reconfiguration capabilities of modern FPGA architectures pave the way for dynamic applications able to adapt to transient events. The CAD flows of modern architectures are nowadays mature but limited by the constraints induced by the complexity of FPGA circuits. In this thesis, multiple contributions are developed to propose an FPGA architecture supporting the dynamic placement of hardware tasks. First, an intermediate representation of these tasks configuration data, independent from their final position, is presented. This representation allows to compress the task data up to 11x with regard to its conventional raw counterpart. An accompanying CAD flow, based on state-of-the-art tools, is proposed to generate relocatable tasks from a high-level description. Then, the online behavior of this mechanism is studied. Two algorithms allowing to decode and create in real-time the conventional bit-stream are described. In addition, an enhancement of the FPGA interconnection network is proposedto increase the placement flexibility of heterogeneous tasks, at the cost of a 10% increase in average of the critical path delay. Eventually, a configurable substitute to the configuration memory found in FPGAs is studied to ease their partial reconfiguration.Les capacités d'auto-reconfiguration des architectures FPGA modernes ouvrent la voie à des applications dynamiques capables d'adapter leur fonctionnement pour répondre à des évènements ponctuels. Les flots de reconfiguration des architectures commerciales sont aujourd'hui aboutis mais limités par des contraintes inhérentes à la complexité de ces circuits. Dans cette thèse, plusieurs contributions sont avancées afin de proposer une architecture FPGA reconfigurable permettant le placement dynamique de tâches matérielles. Dans un premier temps, une représentation intermédiaire des données de configuration de ces tâches, indépendante de leur positionnement final, est présentée. Cette représentation permet notamment d'atteindre des taux de compression allant jusqu'à 11x par rapport à la représentation brute d'une tâche. Un flot de conception basé sur des outils de l'état de l'art accompagne cette représentation et génère des tâches relogeables à partir d'une description haut-niveau. Ensuite, le comportement en ligne de ce mécanisme est étudié. Deux algorithmes permettant le décodage de ces tâches et la génération en temps-réel des données de configuration propres à l'architectures son décrits. Par ailleurs, une amélioration du réseau d'interconnexion d'une architecture FPGA est proposée pour accroître la flexibilité du placement de tâches hétérogènes, avec une augmentation de 10% en moyenne du délai du chemin critique. Enfin, une alternative programmable aux mémoires de configuration de ces circuits est étudiée pour faciliter leur reconfiguration partielle