Collision Avoidance for Mobile Robots with Limited Sensing and Limited Information About the Environment

Phan, Dung; Yang, Junxing; Ratasich, Denise; Grosu, Radu; Smolka, Scott A.; Stoller, Scott D.

doi:10.1007/978-3-319-23820-3_13

Cited by 8 publications

(13 citation statements)

References 8 publications

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“…Modelling the environment is particularly relevant for navigation, and tackling collision avoidance and safe robot navigation [134,31,125,138] often feature in the literature. Although several navigation algorithms exist, some cannot be used in safety-critical scenarios because they have not been verified [134]. The Simplex architecture [154] provides a gateway to using these unverified algorithms with the concept of advanced controllers (AC).…”

Section: Modelling the Physical Environmentmentioning

confidence: 99%

Formal Specification and Verification of Autonomous Robotic Systems

et al. 2019

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Autonomous robotic systems are complex, hybrid, and often safety-critical; this makes their formal specification and verification uniquely challenging. Though commonly used, testing and simulation alone are insufficient to ensure the correctness of, or provide sufficient evidence for the certification of, autonomous robotics. Formal methods for autonomous robotics has received some attention in the literature, but no resource provides a current overview. This paper systematically surveys the state-of-the-art in formal specification and verification for autonomous robotics. Specially, it identifies and categorises the challenges posed by, the formalisms aimed at, and the formal approaches for the specification and verification of autonomous robotics. Introduction, Methodology and Related WorkAn autonomous system is an artificially intelligent entity that makes decisions in response to input, independent of human interaction. Robotic systems are physical entities that interact with the physical world. Thus, we consider an autonomous robotic system as a machine that uses Artificial Intelligence (AI), has a physical presence in and interacts with the real world. They are complex, inherently hybrid, systems, combining both hardware and software; they often require close safety, legal, and ethical consideration. Autonomous robotics are increasingly being used in commonplace-scenarios, such as driverless cars [68], pilotless aircraft [176], and domestic assistants [174,60].While for many engineered systems, testing, either through real deployment or via simulation, is deemed sufficient; the unique challenges of autonomous robotics, their dependence on sophisticated software control and decision-making, and their increasing deployment in safety-critical scenarios, require a stronger form of verification. This leads us towards using formal methods, which are mathematically-based techniques for the specification and verification of software systems, to ensure the correctness of, and provide sufficient evidence for the certification of, robotic systems.We contribute an overview and analysis of the state-of-the-art in formal specification and verification of autonomous robotics. §1.1 outlines the scope, research questions and search criteria for our survey. §1.2 describes related work concerning formal methods for robotics and differentiates them from our work. We recognise the important role that middleware architectures and, non-and semi-formal techniques have in the development of reliable robotics and we briefly summarise some of these techniques in §2. The specification and verification challenges raised by autonomous robotic systems are discussed next: §3 describes the challenges of their context (the external challenges) and §4 describes the challenges of their organisation (the internal challenges). §5 discusses the formalisms used in the literature for specification and verification of autonomous robotics. §6 characterises the approaches to formal specification and verification of autonomous robotics found in the li...

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Section: Modelling the Physical Environmentmentioning

confidence: 99%

Formal Specification and Verification of Autonomous Robotic Systems

et al. 2019

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“…4) The separation between obstacles is such that whenever two adjacent sensors simultaneously detect an obstacle, they are detecting the same obstacle. Assumptions 1-7 about the rover and 1-4 about obstacles are the same as in [28]. This allows us to reuse the Simplex instance in [28] to help ensure the CF property.…”

Section: A Problem Statement and Assumptionsmentioning

confidence: 99%

A Component-Based Simplex Architecture for High-Assurance Cyber-Physical Systems

Phan

Yang

Grosu

et al. 2017

2017 17th International Conference on Application of Concurrency to System Design (ACSD)

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We present Component-Based Simplex Architecture (CBSA), a new framework for assuring the runtime safety of component-based cyber-physical systems (CPSs). CBSA integrates Assume-Guarantee (A-G) reasoning with the core principles of the Simplex control architecture to allow component-based CPSs to run advanced, uncertified controllers while still providing runtime assurance that A-G contracts and global properties are satisfied. In CBSA, multiple Simplex instances, which can be composed in a nested, serial or parallel manner, coordinate to assure system-wide properties.Combining A-G reasoning and the Simplex architecture is a challenging problem that yields significant benefits. By utilizing A-G contracts, we are able to compositionally determine the switching logic for CBSAs, thereby alleviating the state explosion encountered by other approaches. Another benefit is that we can use A-G proof rules to decompose the proof of system-wide safety assurance into sub-proofs corresponding to the componentbased structure of the system architecture. We also introduce the notion of coordinated switching between Simplex instances, a key component of our compositional approach to reasoning about CBSA switching logic.We illustrate our framework with a component-based control system for a ground rover. We formally prove that the CBSA for this system guarantees energy safety (the rover never runs out of power), and collision freedom (the rover never collides with a stationary obstacle). We also consider a CBSA for the rover that guarantees mission completion: all target destinations visited within a prescribed amount of time.

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“…Prior approaches [1,3,7,9] focus on modeling and verification techniques to ensure collision safety for autonomous systems in dynamic or unknown environments. Other works [8] present a more including approach, which reflects on the whole spectrum of cyber-physical systems.…”

Section: Related Workmentioning

confidence: 99%

“…Phan et al [9] present a runtime approach based on the Simplex architecture [11], to ensure collisionfreedom for robots with limited field-of-view and limited sensing range in unknown environments, i.e. environments where the detailed shapes and the locations of the obstacles are not known in advance.…”

Section: Related Workmentioning

confidence: 99%

Towards the Verification of Safety-critical Autonomous Systems in Dynamic Environments

Aniculăesei

Arnsberger

Howar

et al. 2016

Electron. Proc. Theor. Comput. Sci.

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There is an increasing necessity to deploy autonomous systems in highly heterogeneous, dynamic environments, e.g. service robots in hospitals or autonomous cars on highways. Due to the uncertainty in these environments, the verification results obtained with respect to the system and environment models at design-time might not be transferable to the system behavior at run time. For autonomous systems operating in dynamic environments, safety of motion and collision avoidance are critical requirements. With regard to these requirements, Maček et al. [6] define the passive safety property, which requires that no collision can occur while the autonomous system is moving. To verify this property, we adopt a two phase process which combines static verification methods, used at design time, with dynamic ones, used at run time. In the design phase, we exploit UPPAAL to formalize the autonomous system and its environment as timed automata and the safety property as TCTL formula and to verify the correctness of these models with respect to this property. For the runtime phase, we build a monitor to check whether the assumptions made at design time are also correct at run time. If the current system observations of the environment do not correspond to the initial system assumptions, the monitor sends feedback to the system and the system enters a passive safe state.

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Collision Avoidance for Mobile Robots with Limited Sensing and Limited Information About the Environment

Cited by 8 publications

References 8 publications

Formal Specification and Verification of Autonomous Robotic Systems

Formal Specification and Verification of Autonomous Robotic Systems

A Component-Based Simplex Architecture for High-Assurance Cyber-Physical Systems

Towards the Verification of Safety-critical Autonomous Systems in Dynamic Environments

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