Formal Verification of an Autonomous Personal Robotic Assistant

Human–robot teams are likely to be used in a variety of situations wherever humans require the assistance of robotic systems. Obvious examples include healthcare and manufacturing, in which people need the assistance of machines to perform key tasks. It is essential for robots working in close proximity to people to be both safe and trustworthy. In this paper we examine formal verification of a high-level planner/scheduler for autonomous personal robotic assistants such as CareO-bot. We describe how a model of Care-O-bot and its environment was developed using Brahms, a multiagent workflow language. Formal verification was then carried out by translating this to the input language of an existing model checker. Finally we present some formal verification results and describe how these could be complemented by simulation-based testing and realworld end-user validation in order to increase the practical and perceived safety and trustworthiness of robotic assistants

Formal Verification of Synchronisation, Gossip and Environmental Effects for Wireless Sensor Networks

The Internet of Things (IoT) promises a revolution in the monitoring and control of a wide range of applications, from urban water supply networks and precision agriculture food production, to vehicle connectivity and healthcare monitoring. For applications in such critical areas, control software and protocols for IoT systems must be verified to be both robust and reliable. Two of the largest obstacles to robustness and reliability in IoT systems are effects on the hardware caused by environmental conditions, and the choice of parameters used by the protocol. In this paper we use probabilistic model checking to verify that a synchronisation and dissemination protocol for Wireless Sensor Networks (WSNs) is correct with respect to its requirements, and is not adversely affected by the environment. We show how the protocol can be converted into a logical model and then analysed using the probabilistic model-checker, PRISM. Using this approach we prove under which circumstances the protocol is guaranteed to synchronise all nodes and disseminate new information to all nodes. We also examine the bounds on synchronisation as the environment changes the performance of the hardware clock, and investigate the scalability constraints of this approach

Assembly of splicing complexes on exon 11 of the human insulin receptor gene does not correlate with splicing efficiency in-vitro

BACKGROUND: Incorporation of exon 11 of the insulin receptor gene is both developmentally and hormonally-regulated. Previously, we have shown the presence of enhancer and silencer elements that modulate the incorporation of the small 36-nucleotide exon. In this study, we investigated the role of inherent splice site strength in the alternative splicing decision and whether recognition of the splice sites is the major determinant of exon incorporation. RESULTS: We found that mutation of the flanking sub-optimal splice sites to consensus sequences caused the exon to be constitutively spliced in-vivo. These findings are consistent with the exon-definition model for splicing. In-vitro splicing of RNA templates containing exon 11 and portions of the upstream intron recapitulated the regulation seen in-vivo. Unexpectedly, we found that the splice sites are occupied and spliceosomal complex A was assembled on all templates in-vitro irrespective of splicing efficiency. CONCLUSION: These findings demonstrate that the exon-definition model explains alternative splicing of exon 11 in the IR gene in-vivo but not in-vitro. The in-vitro results suggest that the regulation occurs at a later step in spliceosome assembly on this exon

Probabilistic Model Checking of Robots Deployed in Extreme Environments

Robots are increasingly used to carry out critical missions in extreme environments that are hazardous for humans. This requires a high degree of operational autonomy under uncertain conditions, and poses new challenges for assuring the robot's safety and reliability. In this paper, we develop a framework for probabilistic model checking on a layered Markov model to verify the safety and reliability requirements of such robots, both at pre-mission stage and during runtime. Two novel estimators based on conservative Bayesian inference and imprecise probability model with sets of priors are introduced to learn the unknown transition parameters from operational data. We demonstrate our approach using data from a real-world deployment of unmanned underwater vehicles in extreme environments.Comment: Version accepted at the 33rd AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, 201

Formal Verification of Astronaut-Rover Teams for Planetary Surface Operations

This paper describes an approach to assuring the reliability of autonomous systems for Astronaut-Rover (ASRO) teams using the formal verification of models in the Brahms multi-agent modelling language. Planetary surface rovers have proven essential to several manned and unmanned missions to the moon and Mars. The first rovers were tele- or manuallyoperated, but autonomous systems are increasingly being used to increase the effectiveness and range of rover operations on missions such as the NASA Mars Science Laboratory. It is anticipated that future manned missions to the moon and Mars will use autonomous rovers to assist astronauts during extravehicular activity (EVA), including science, technical and construction operations. These ASRO teams have the potential to significantly increase the safety and efficiency of surface operations. We describe a new Brahms model in which an autonomous rover may perform several different activities including assisting an astronaut during EVA. These activities compete for the autonomous rovers “attention’ and therefore the rover must decide which activity is currently the most important and engage in that activity. The Brahms model also includes an astronaut agent, which models an astronauts predicted behaviour during an EVA. The rover must also respond to the astronauts activities. We show how this Brahms model can be simulated using the Brahms integrated development environment. The model can then also be formally verified with respect to system requirements using the SPIN model checker, through automatic translation from Brahms to PROMELA (the input language for SPIN). We show that such formal verification can be used to determine that mission- and safety critical operations are conducted correctly, and therefore increase the reliability of autonomous systems for planetary rovers in ASRO teams

Use and usability of software verification methods to detect behaviour interference when teaching an assistive home companion robot: A proof-of-concept study

© 2021 Kheng Lee Koay et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 International License. https://creativecommons.org/licenses/by/4.0/When studying the use of assistive robots in home environments, and especially how such robots can be personalised to meet the needs of the resident, key concerns are issues relating to behaviour verification, behaviour interference and safety. Here, personalisation refers to the teaching of new robot behaviours by both technical and non-technical end users. In this article we consider the issue of behaviour interference caused by situations where newly taught robot behaviours may affect or be affected by existing behaviours and thus, those behaviours will not or might not ever be executed. We focus in particular on how such situations can be detected and presented to the user. We describe the human-robot behaviour teaching system that we developed as well as the formal behaviour checking methods used. The online use of behaviour checking is demonstrated, based on static analysis of behaviours during the operation of the robot, and evaluated in a user study. We conducted a proof of concept human-robot interaction study with an autonomous, multi-purpose robot operating within a smart home environment. Twenty participants individually taught the robot behaviours according to instructions they were given, some of which caused interference with other behaviours. A mechanism for detecting behaviour interference provided feedback to participants and suggestions on how to resolve those conflicts. We assessed the participants’ views on detected interference as reported by the behaviour teaching system. Results indicate that interference warnings given to participants during teaching provoked an understanding of the issue. We did not find a significant influence of participants’ technical background. These results highlight a promising path towards verification and validation of assistive home companion robots that allow end-user personalisation.Peer reviewe

Meta-analyses support a taxonomic model for representations of different categories of audio-visual interaction events in the human brain

Our ability to perceive meaningful action events involving objects, people and other animate agents is characterized in part by an interplay of visual and auditory sensory processing and their cross-modal interactions. However, this multisensory ability can be altered or dysfunctional in some hearing and sighted individuals, and in some clinical populations. The present meta-analysis sought to test current hypotheses regarding neurobiological architectures that may mediate audio-visual multisensory processing. Reported coordinates from 82 neuroimaging studies (137 experiments) that revealed some form of audio-visual interaction in discrete brain regions were compiled, converted to a common coordinate space, and then organized along specific categorical dimensions to generate activation likelihood estimate (ALE) brain maps and various contrasts of those derived maps. The results revealed brain regions (cortical “hubs”) preferentially involved in multisensory processing along different stimulus category dimensions, including (1) living versus non-living audio-visual events, (2) audio-visual events involving vocalizations versus actions by living sources, (3) emotionally valent events, and (4) dynamic-visual versus static-visual audio-visual stimuli. These meta-analysis results are discussed in the context of neurocomputational theories of semantic knowledge representations and perception, and the brain volumes of interest are available for download to facilitate data interpretation for future neuroimaging studies

Verifiable self-certifying autonomous systems

Autonomous systems are increasingly being used in safety-and mission-critical domains, including aviation, manufacturing, healthcare and the automotive industry. Systems for such domains are often verified with respect to essential requirements set by a regulator, as part of a process called certification. In principle, autonomous systems can be deployed if they can be certified for use. However, certification is especially challenging as the condition of both the system and its environment will surely change, limiting the effective use of the system. In this paper we discuss the technological and regulatory background for such systems, and introduce an architectural framework that supports verifiably-correct dynamic self-certification by the system, potentially allowing deployed systems to operate more safely and effectively