Characterizing and evaluating autonomous controllers

Premio Extraordinario de Doctorado de la UAH en el año académico 2016-2017La autonomía en robótica por medio de técnicas de Inteligencia Artificial, particularmente mediante el empleo sistemas de Planning & Scheduling (P&S), presenta un amplio campo de investigación con gran interés en aplicaciones como la robótica de exploración para entornos hostiles o difícilmente accesibles para los humanos. Sin embargo, las pruebas experimentales realizadas en los artículos de divulgación científica sobre controladores autónomos generalmente no están correctamente realizadas, ya que se carece de una metodología de estudio común. En este sentido se hace complicado comparar los nuevos sistemas con los trabajos previos, práctica habitual en otras disciplinas. Por ello, en esta tesis se propone un entorno de trabajo llamado On-Ground Autonomy Test Environment (OGATE) para permitir la evaluación de controladores autónomos. Este desarrollo consta de una metodología para estructurar la fase experimental, así como de un conjunto de métricas independientes tanto del dominio como del campo de aplicación del sistema robótico. La unión de estos elementos, mediante un software que automatiza el proceso experimental, permite obtener evaluaciones reproducibles y objetivas sobre los controladores autónomos bajo estudio. Para demostrar la efectividad del entorno de trabajo, se han utilizado dos controladores autónomos basados en diferentes paradigmas para P&S. Primero se ha utilizado el Goal Oriented Autonomous Controller (GOAC), desarrollado bajo contrato de la Agencia Espacial Europea. Segundo, durante esta tesis se ha implementado la Model-Based Architecture (MoBAr). MoBAr está diseñado con el objetivo de probar diferentes planificadores basados en el Planning Domain Definition Language (PDDL) para conseguir autonomía a bordo. En este sentido, en la tesis también se introduce un nuevo planificador llamado Unified Path Planning and Task Planning Architecture (UP2TA). Dicho sistema integra un planificador general basado en PDDL y algoritmos de planificación de rutas con el objetivo de generar planes más seguros y eficientes para robots de exploración. Referente a la planificación de rutas, en la tesis se incluye la definición de dos nuevos algoritmos enfocados en la movilidad de los robots de exploración: S-Theta* y 3D Accurate Navigation Algorithm (3Dana). S-Theta* permite obtener rutas con un menor número de cambios de dirección que algoritmos previos, mientras que 3Dana genera rutas más seguras y restringidas en función de la pendiente del entorno, empleando para ello Modelos Digitales de Terreno (MDT) y mapas de costes trasversales. Partiendo de GOAC y MoBAr, se ha empleado OGATE para evaluar ambos controladores, siendo posible caracterizar aspectos relevantes de la integración entre Planning & Execution (P&E) difícilmente accesibles mediante otros enfoques. Además, los resultados obtenidos son objetivos y reproducibles, permitiendo realizar comparaciones entre controladores autónomos con diferentes tecnologías y/o paradigmas de P&S

Configuration of skilled tasks for execution in multipurpose and collaborative service robots

Several highly versatile mobile robots have been introduced during the last ten years. Some of these robots are working among people in exhibitions and other public places, such as museums and shopping centers. Unlike industrial robots, which are typically found only in manufacturing environments, service robots can be found in a variety of places, ranging from homes to offices, and from hospitals to restaurants. Developing mobile robots working co-operatively with humans raises not only interaction problems but problems in getting tasks accomplished. In an unstructured and dynamic environment this is not readily achievable because of the high degree of complexity of perception and motion of the robots. Such tasks require high-level perception and locomotion systems, not to mention control systems for all levels of task control. The lowest levels are controlling the motors and sensors of the robots and the highest are sophisticated task planners for complex and useful tasks. Human-friendly communication can be seen as an important factor in getting robots into our homes. In this work a new task configuration concept is proposed for multipurpose service robots. The concept gives guidelines for a software architecture and task managing system. Task configuration process presents a new method which makes it easier to configure a new task for a robot. The idea is the same as when a person tells another how a task should be performed. Novel method for executing tasks with service robots is also presented. Interpretive execution, keeping the focus on only one micro task at a time, makes it possible to modify plans during their execution. Multimodal interaction is important feature to provide collaboration between humans and robots. Multimodal interaction reduces the workload of the user by administering task configuration and execution. A novel solution for using multimodal human-robot interaction (HRI) as a part of the task description is presented. This thesis is a case study reporting the results when developing a task managing (from configuring to execution) platform for multipurpose service robots and studying its performance and use with several test cases. The platform that was developed has been implemented with the WorkPartner multipurpose service robot. The structure and operation of the platform have proved to be useful and several tasks have been carried out successfully

Engineering Challenges Ahead for Robot Teamwork in Dynamic Environments

Gefördert durch den Publikationsfonds der Universität Kasse

Automated Hierarchical, Forward-Chaining Temporal Planner for Planetary Robots Exploring Unknown Environments

The transition of mobile robots from a controlled environment towards the real-world represents a major leap in terms of complexity coming primarily from three different factors: partial observability, nondeterminism and dynamic events. To cope with them, robots must achieve some intelligence behaviours to be cost and operationally effective. Two particularly interesting examples of highly complex robotic scenarios are Mars rover missions and the Darpa Robotic Challenge (DRC). In spite of the important differences they present in terms of constraints and requirements, they both have adopted certain level of autonomy to overcome some specific problems. For instance, Mars rovers have been endowed with multiple systems to enable autonomous payload operations and consequently increase science return. In the case of DRC, most teams have autonomous footstep planning or arm trajectory calculation. Even though some specific problems can be addressed with dedicated tools, the general problem remains unsolved: to deploy on-board a reliable reasoning system able to operate robots without human intervention even in complex environments. This is precisely the goal of an automated mission planner. The scientific community has provided plenty of planners able to provide very fast solutions for classical problems, typically characterized by the lack of time and resources representation. Moreover, there are also a handful of applied planners with higher levels of expressiveness at the price of lowest performance. However, a fast, expressive and robust planner has never been used in complex robotic missions. These three properties represent the main drivers for the outcomes of the thesis. To bridge the gap between classical and applied planning, a novel formalism named Hierarchical TimeLine Networks (HTLN) combining Timeline and HTN planning has been proposed. HTLN has been implemented on a mission planner named QuijoteExpress, the first forward-chaining timeline planner to the best of our knowledge. The main idea is to benefit from the great performance of forward-chaining search to resolve temporal problems on the state-space. In addition, QuijoteExpress includes search enhancements such as parallel planning by division of the problem in sub-problems or advanced heuristics management. Regarding expressiveness, the planner incorporates HTN techniques that allow to define hierarchical models and solutions. Finally, plan robustness in uncertain scenarios has been addressed by means of sufficient plans that allow to leave parts of valid plans undefined. To test the planner, a novel lightweight, timeline and ROS-based executive named SanchoExpress has been designed to translate the plans into actions understandable by the different robot subsystems. The entire approach has been tested in two realistic and complementary domains. A cooperative multirover Mars mission and an urban search and rescue mission. The results were extremely positive and opens new promising ways in the field of automated planning applied to robotics

RoboArch: Architectural Modelling for Robotic Applications

Robotic systems are being employed in a diverse range of applications, with both the scale and complexity of their software increasing through having to operate in unstructured environments and to provide higher levels of autonomy. In addition, the need for robotic systems to be verified grows as robots are used in applications where they can have significant safety implications. Verification of even small robotic systems software is a challenging problem. Therefore, additional techniques are required to enable the practitioners to produce verified robotic systems. The use of model-driven engineering and domain-specific languages (DSLs) have proven useful in the development of complex systems in other areas so applying them to the field of robotics can contribute to the goal of building reliable and safe systems. In this thesis we present RoboArch, a notation for describing the architectures and patterns of robotic systems software supported by the formally defined semantics of RoboChart. RoboChart is a DSL for modelling the behaviour of robot software controllers using state machines. We describe RoboArch from the top-down. First, we examine the role of robotics software architectures in the development of robotic systems by reviewing five robotics architectures, and five DSLs. Next, for the layered architectural pattern, the RoboArch notation is introduced; we provide a metamodel, well-formedness conditions, and transformation rules to RoboChart. Further, we characterise two patterns: reactive skills and subsumption, which can be used by a layer. Finally, we discuss a tool and its implementation for the evaluation of RoboArch and automation of the rules as model transformations. We use a case study of a small obstacle avoidance system to demonstrate: the application of the reactive skills pattern using RoboArch and the expected properties of the architecture that can be proven using the generated RoboChart model CSP semantics

Engineering trust in space with runtime verification

Spaceborne systems must contend with extreme operating environments and tight resource limits while satisfying risk-averse programs developing limited production runs. These constraints naturally encourage a Cyber-Physical System (CPS) architecture wherein control is distributed across a network of embedded controllers arranged in a hierarchy, a design pattern also seen in contemporary robotics, drone aircraft, and autonomous cars. Since each controller is tightly coupled to the system's physical state and cross-coupled to the state of the other controllers, even simple CPS can exhibit complex behavior with inseparable physical (continuous) and logical (discrete) dynamics. Technical evidence that a system will meet safety and mission assurance expectations, i.e., engineering trust, must be evaluated before deployment. However, traditional methods of engineering trust depend on accumulated experience, enumeration of failure modalities, exhaustive test coverage, or assumptions of composability that may not transfer, scale, or hold when developing novel cyber-physical systems. These limitations are compounded in the space domain as exploration pushes further from Earth - necessitating more autonomy - and by more advanced mission architectures that require complex heterogeneous systems-of-systems or swarms of spacecraft to accomplish their purpose. Formal methods have successfully provided assurances in CPSs beyond the limitations of traditional methods. While industrial adoption lags behind the state-of-the-art, the cost-benefit trade of formal method verification suits the space domain where higher per-unit costs are expected, operational resources are constrained, and the system must meet strict robustness requirements under unanticipated operating conditions. Of particular interest is Runtime Verification (RV), a lightweight formal method that evaluates a system's current state and trajectory (rather than all possible states and trajectories) and can be implemented with bounded resource requirements, bringing the mathematical certainty of formal methods onboard flight systems for trust in real-time. We evaluate the suitability of runtime verification for use in spaceborne cyber-physical systems by adapting the R2U2 hardware RV engine to address an emergent fault on board Robonaut2, including improving the monitor's memory requirements and encoding the faulty behavior as a Mission-time Linear Temporal Logic (MLTL) specification. From this experience, we identify five steps for adopting RV in a CPS: semantics, encoding, extension, implementation, and integration. We work to advance the capabilities of RV across all five identified steps, emphasizing usability by subject-matter experts without formal methods experience and the unique requirements of space flight systems. Our results include new language extensions to improve reasoning efficiency and specification ergonomics, monitor features to support common verification patterns like Assume-Guarantee Contracts (AGCs), improvements to the computational efficiency of the monitor, examples of encoding "impossible" specifications by leveraging implied constraints, and experience reports preparing software to graduate from academia to industrial use. We assess the suitability and usability of these changes through the experience of our industry partners who have selected R2U2 for use by the Vehicle Systems Manager (VSM) component of NASA's Lunar Gateway space station. This work culminates in a new software version of the R2U2 runtime verification monitor for VSM designed to meet the exacting requirements of engineering trust in human spaceflight, incorporating our feature improvements and their feedback. Building on these results, we present early-stage work extending RV to multi-agent Distributed Space Systems (DSS), which includes the interaction between multiple vehicles in the hierarchy of CPS nodes and drops the assumption of perfect communication accordingly. Crucially, we retain the view of the entire CPS as a single entity, i.e., just as Robonaut2 and Gateway are considered a single CPS comprised of subsystems, we regard the whole swarm of satellites as a single system