On Using Formal Methods For Safe And Robust Robot Autonomy
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On Using Formal Methods For Safe And Robust Robot Autonomy
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Author : Karen Yan Ming Leung
language : en
Publisher:
Release Date : 2021
On Using Formal Methods For Safe And Robust Robot Autonomy written by Karen Yan Ming Leung and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Advances in the fields of artificial intelligence and machine learning have unlocked a new generation of robotic systems--"learning-enabled" robots that are designed to operate in unstructured, uncertain, and unforgiving environments, especially settings where robots are required to interact in close proximity with humans. However, as learning-enabled methods, especially "deep" learning, continue to become more pervasive throughout the autonomy stack, it also becomes increasingly difficult to ascertain the performance and safety of these robotic systems and explain their behavior, necessary prerequisites for their deployment in safety-critical settings. This dissertation develops methods drawing upon techniques from the field of formal methods, namely Hamilton-Jacobi (HJ) reachability and Signal Temporal Logic (STL), to complement a learning-enabled robot autonomy stack, thereby leading to safer and more robust robot behavior. The first part of this dissertation investigates the problem of providing safety assurance for human-robot interactions, safety-critical settings wherein robots must reason about the uncertainty in human behavior to achieve seamless interactions with humans. Specifically, we develop a two-step approach where we first develop a learning-based human behavior prediction model tailored towards proactive robot planning and decision-making, which we then couple with a reachability-based safety controller that minimally intervenes whenever the robot is near safety violation. The approach is validated through human-in-the-loop simulation as well as on an experimental vehicle platform, demonstrating clear connections between theory and practice. The second part of this dissertation examines the use of STL as a formal language to incorporate logical reasoning into robot learning. In particular, we develop a technique, named STLCG, that casts STL into the same computational language as deep neural networks. Consequently, by using STLCG to express designers' domain expertise into a form compatible with neural networks, we can embed domain knowledge into learned components within the autonomy stack to provide additional levels of robustness and interpretability.
Robust Control Planning And Inference For Safe Robot Autonomy
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Author : Sumeet Singh
language : en
Publisher:
Release Date : 2019
Robust Control Planning And Inference For Safe Robot Autonomy written by Sumeet Singh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Integrating autonomous robots into safety-critical settings requires reasoning about uncertainty at all levels of the autonomy stack. This thesis presents novel algorithmic tools for imbuing robustness within two hierarchically complementary areas, namely: motion planning and decision-making. In Part I of the thesis, by harnessing the theories of contraction and semi-infinite convex optimization and the computational tool of sum-of-squares programming, we present a unified framework for robust real-time motion planning for complex underactuated nonlinear systems. Broadly, the approach entails pairing open-loop motion planning algorithms that neglect uncertainty and are optimized for generating trajectories for simple kinodynamic models in real-time, with robust nonlinear trajectory-tracking feedback controllers. We demonstrate how to systematically synthesize these controllers and integrate them within planning to generate and execute certifiably safe trajectories that are robust to the closed-loop effects of disturbances and planning with simplified models. In Part II of the thesis, we demonstrate how to embed the control-theoretic advancements developed in Part I as constraints within a novel semi-supervised algorithm for learning dynamical systems from user demonstrations. The constraints act as a form of context-driven hypothesis pruning to yield learned models that jointly balance regression performance and stabilizability, ultimately resulting in generated trajectories for the robot that are conditioned for feedback control. Experimental results on a quadrotor testbed illustrate the efficacy of the proposed algorithms in Parts I and II of the thesis, and clear connections between theory and hardware. Finally, in Part III of the thesis, we describe a framework for lifting notions of robustness from low-level motion planning to higher-level sequential decision-making using the theory of risk measures. Leveraging a class of risk measures with favorable axiomatic foundations, we demonstrate how to formulate decision-making algorithms with tunable robustness properties. In particular, we focus on a novel application of this framework to inverse reinforcement learning where we learn predictive motion models for humans in safety-critical scenarios, and illustrate their effectiveness within a commercial driving simulator featuring humans in-the-loop. The contributions within this thesis constitute an important step towards endowing modern robotic systems with the ability to systematically and hierarchically reason about safety and efficiency in the face of uncertainty, which is crucial for safety-critical applications.
Enabling Safe And Robust Control Of Robots Via Hamilton Jacobi Reachability
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Author : Anjian Li
language : en
Publisher:
Release Date : 2020
Enabling Safe And Robust Control Of Robots Via Hamilton Jacobi Reachability written by Anjian Li and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
As autonomous robots become pervasive in daily life, it is important to ensure they successfully accomplish the task while being safe from collisions. These desired behaviours require both perception of the environment and robust control of the robot. Traditional optimal control method Hamilton-Jacobi (HJ) Reachability can formally verify the safety of the robot, but requires an a priori known map and is computationally intractable for high dimensional systems. Machine learning is widely used in machine perception, and recently, End-to-End method has been proposed to bridge the perception and control for robotics. However, it suffers from data inefficiency and lack of robustness when applied to robotics tasks. To address the above challenges, firstly we propose a theoretical improvement on approximating HJ Reachability. Our novel system decomposition technique largely reduces the computation complexity without introducing much conservatism. Both formal mathematical proof and numerical examples are provided to demonstrate its efficiency and guaranteed-safe property. We also present the first HJ Reachability analysis on 6D bicycle model that is previously considered intractable. Secondly, we apply HJ Reachability to learning-based visual navigation in indoor office environment, where a convolutional neural network (CNN) processes the visual input and predicts waypoint that leads to the goal. We propose a novel cost function for waypoint evaluation and generation based on HJ Reachability analysis, and uses disturbances in dynamics to model CNN's prediction error. Compared to state-of-the-art, our method shows more robust behaviours when navigating in narrow spaces demonstrated in both the simulation and hardware experiment in SFU buildings.
Verifiable Autonomous Systems
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Author : Louise A. Dennis
language : en
Publisher: Cambridge University Press
Release Date : 2023-04-30
Verifiable Autonomous Systems written by Louise A. Dennis and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-30 with Computers categories.
A discussion of methods by which scientists may guarantee the behaviours of autonomous systems, from intelligent robots to driverless cars.
Robust Robotic Manipulation For Effective Multi Contact And Safe Physical Interactions
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Author : Mikael Daniel Gabriel Jorda
language : en
Publisher:
Release Date : 2020
Robust Robotic Manipulation For Effective Multi Contact And Safe Physical Interactions written by Mikael Daniel Gabriel Jorda and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Robots are complex systems, at the intersection of numerous engineering domains. The goal of many researchers is to build a fully capable and safe robot that can work and assist humans in their daily lives. To reach these goals, the complex robotic systems must be separated in different subsystem components such as perception, world understanding, navigation, manipulation, interfaces and interaction. These subsystems need to be safe and robust in order to synergistically work together. In particular, a reliable and general robot manipulation framework for free space and contact tasks is required for robots to become useful in new environments. In this thesis, we aim at developing a theoretical and practical foundation for safe and robust robotic manipulation, involving multiple simultaneous physical interactions with complex and unknown environments. We start with the well known operational space control framework: a task-oriented control methodology that enables task dynamic decoupling and hierarchical control structures. After reviewing the operational space control theory for controlling a robot task and posture, we present a series of practical considerations for its robust implementation on real hardware platforms. The integration in this framework of constraints such as joint limits and obstacles is then discussed, and a method to react safely to unexpected contacts on the robot structure during operations is proposed. These constraints are handled as control objectives in the control hierarchy, using artificial potential fields to generate repulsive forces and dynamically consistent projections to ensure an independent control of the constraints and task objectives. This systematic treatment of constraints at the control level enables a robust, autonomous execution of complex tasks in changing environments. This framework was extended over the years to consider underactuated robots in arbitrary contact situations. This resulted in a comprehensive formulation to the problem of controlling a high-dimensional robotic system involving complex tasks subject to various constraints, obstacles, balance and multiple contacts. Contacts are essential for robot manipulation. On the one hand, parts of the robot tasks involve physical interactions that need to be controlled precisely. On the other hand, further contacts are required on underactuated systems in order to enable the robot motion and guarantee its balance. In addition, contacts between the robot and the environment are subject to geometric and friction constraints that need to be addressed by the control framework. Therefore, in this thesis, the operational space whole-body control framework is completed to enable a systematic treatment of multi-contact scenarios. A virtual linkage model separates the contact forces into three sets. The resultant forces allow the robot to compensate for its underactuation. The task contact forces are controlled to their desired values. The internal forces provide a way to satisfy geometric and friction constraints. A method using barrier functions is proposed to specify a set of internal forces that ensure the robot's balance and contact stability. Even when the desired contact forces are correctly specified, their control remains a challenge. Indeed, the fast and discontinuous closed loop dynamics of stiff physical interactions leads to instabilities in robot force control. Therefore, we adapt a time domain passivity approach to guarantee the stability of explicit force controllers. This results in an increased robustness and safety for robotic systems in multiple contact scenarios. To develop effective interfaces for human-robot collaboration, we also study haptic robot teleoperation. Haptic devices provide an intuitive interface to remotely control robots and combine the high-level cognitive autonomy of humans with the autonomous manipulation capabilities of robots. The goal of haptic robot control is to maximize the transparency between the human operator and the robot environment. It means that the robot environment should be felt by the human as if they were directly interacting with it, and the human commands should be executed precisely by the robot. Transparency is very challenging to achieve when communication delays are present in the system, which occurs systematically when there is a significant physical distance between the controlled robot and its human operator. To address this challenge, we propose a new paradigm for performing haptic-robot control. Instead of relying on a global feedback loop, the new method establishes two autonomous controllers acting on the robot and the haptic device, interfaced via a dual-proxy model. The dual-proxy is a bridge between the local controllers. It generates appropriate motion and force inputs that are consistent with the task physical interactions. The model relies on the exchange of position, contact, and environment geometry information, avoiding the limitations caused by a direct force feedback between robot and haptic device in conventional teleoperation. To estimate the environment contact geometry in real-time, we also design a new perception algorithm that enables a fully autonomous implementation of the dual-proxy model. The performance of all the control methods presented in this thesis are evaluated via simulations and hardware experimental validation. Combining these methods together results in a robust, safe and generic manipulation control framework for complex robots in interaction with uncertain environments. Such framework is one of the key components for a complete and fully capable robotic system.
Agents And Robots For Reliable Engineered Autonomy
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Author : Rafael C Cardoso
language : en
Publisher: Mdpi AG
Release Date : 2021-09-10
Agents And Robots For Reliable Engineered Autonomy written by Rafael C Cardoso and has been published by Mdpi AG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-10 with Technology & Engineering categories.
This book contains the contributions of the Special Issue entitled "Agents and Robots for Reliable Engineered Autonomy". The Special Issue was based on the successful first edition of the "Workshop on Agents and Robots for reliable Engineered Autonomy" (AREA 2020), co-located with the 24th European Conference on Artificial Intelligence (ECAI 2020). The aim was to bring together researchers from autonomous agents, as well as software engineering and robotics communities, as combining knowledge from these three research areas may lead to innovative approaches that solve complex problems related to the verification and validation of autonomous robotic systems.
Formal Methods For Autonomous Systems
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Author : Tichakorn Wongpiromsarn
language : en
Publisher:
Release Date : 2023-09-21
Formal Methods For Autonomous Systems written by Tichakorn Wongpiromsarn and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-21 with Computers categories.
Formal methods refer to rigorous, mathematical approaches to system development and have played a key role in establishing the correctness of safety-critical systems. The main building blocks of formal methods are models and specifications, which are analogous to behaviors and requirements in system design and give us the means to verify and synthesize system behaviors with formal guarantees. In this monograph the authors review the current state of the art of applications of formal methods in the autonomous systems domain. They first consider correct-by-construction synthesis under various formulations in known environments before addressing the concept of uncertainty with systems that employ learning using formal methods including overcoming some limitations of such systems. Finally, they examine the synthesis of systems with monitoring to ensure a system can return to normalcy. They conclude with future directions for formal methods in reinforcement learning, uncertainty, privacy, explainability of formal methods, and regulation and certification. Covering important topics such as synthesis and reinforcement learning it is a comprehensive resource for students, practitioners and researchers on the use of formal methods in modern systems.
Autonomy Requirements Engineering For Space Missions
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Author : Emil Vassev
language : en
Publisher: Springer
Release Date : 2014-08-27
Autonomy Requirements Engineering For Space Missions written by Emil Vassev and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-27 with Computers categories.
Advanced space exploration is performed by unmanned missions with integrated autonomy in both flight and ground systems. Risk and feasibility are major factors supporting the use of unmanned craft and the use of automation and robotic technologies where possible. Autonomy in space helps to increase the amount of science data returned from missions, perform new science, and reduce mission costs. Elicitation and expression of autonomy requirements is one of the most significant challenges the autonomous spacecraft engineers need to overcome today. This book discusses the Autonomy Requirements Engineering (ARE) approach, intended to help software engineers properly elicit, express, verify, and validate autonomy requirements. Moreover, a comprehensive state-of-the-art of software engineering for aerospace is presented to outline the problems handled by ARE along with a proof-of-concept case study on the ESA's BepiColombo Mission demonstrating the ARE’s ability to handle autonomy requirements.
Autonomous Mobile Robots
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Author : Frank L. Lewis
language : en
Publisher: CRC Press
Release Date : 2018-10-03
Autonomous Mobile Robots written by Frank L. Lewis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Technology & Engineering categories.
It has long been the goal of engineers to develop tools that enhance our ability to do work, increase our quality of life, or perform tasks that are either beyond our ability, too hazardous, or too tedious to be left to human efforts. Autonomous mobile robots are the culmination of decades of research and development, and their potential is seemingly unlimited. Roadmap to the Future Serving as the first comprehensive reference on this interdisciplinary technology, Autonomous Mobile Robots: Sensing, Control, Decision Making, and Applications authoritatively addresses the theoretical, technical, and practical aspects of the field. The book examines in detail the key components that form an autonomous mobile robot, from sensors and sensor fusion to modeling and control, map building and path planning, and decision making and autonomy, and to the final integration of these components for diversified applications. Trusted Guidance A duo of accomplished experts leads a team of renowned international researchers and professionals who provide detailed technical reviews and the latest solutions to a variety of important problems. They share hard-won insight into the practical implementation and integration issues involved in developing autonomous and open robotic systems, along with in-depth examples, current and future applications, and extensive illustrations. For anyone involved in researching, designing, or deploying autonomous robotic systems, Autonomous Mobile Robots is the perfect resource.
Safe Autonomy With Control Barrier Functions
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Author : Wei Xiao
language : en
Publisher: Springer Nature
Release Date : 2023-05-09
Safe Autonomy With Control Barrier Functions written by Wei Xiao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-09 with Technology & Engineering categories.
This book presents the concept of Control Barrier Function (CBF), which captures the evolution of safety requirements during the execution of a system and can be used to enforce safety. Safety is formalized using an emerging state-of-the-art approach based on CBFs, and many illustrative examples from autonomous driving, traffic control, and robot control are provided. Safety is central to autonomous systems since they are intended to operate with minimal or no human supervision, and a single failure could result in catastrophic results. The authors discuss how safety can be guaranteed via both theoretical and application perspectives. This presented method is computationally efficient and can be easily implemented in real-time systems that require high-frequency reactive control. In addition, the CBF approach can easily deal with nonlinear models and complex constraints used in a wide spectrum of applications, including autonomous driving, robotics, and traffic control. With the proliferation of autonomous systems, such as self-driving cars, mobile robots, and unmanned air vehicles, safety plays a crucial role in ensuring their widespread adoption. This book considers the integration of safety guarantees into the operation of such systems including typical safety requirements that involve collision avoidance, technological system limitations, and bounds on real-time executions. Adaptive approaches for safety are also proposed for time-varying execution bounds and noisy dynamics.