Model-Based Adaptation for Robotics Software

Aldrich, Jonathan; Garlan, David; Kaestner, Christian; Goues, Claire Le; Mohseni-Kabir, Anahita; Ruchkin, Ivan; Samuel, Selva; Schmerl, Bradley; Timperley, Christopher Steven; Veloso, Manuela; Voysey, Ian; Biswas, Joydeep; Guha, Arjun; Holtz, Jarrett; Cámara, Javier; Jamshidi, Pooyan

doi:10.1109/ms.2018.2885058

Cited by 20 publications

(17 citation statements)

References 6 publications

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“…This concept was inspired from the biological adaptation which is defined as the process of adapting to a certain environment to survive. In the same way, the adaptation of an agent in complex adaptive systems is the change of strategy in order to survive and guarantee the correct performance of its tasks (Aldrich et al 2019). The following state diagram in Fig.…”

Section: Adaptationmentioning

confidence: 99%

Formal approach to model complex adaptive computing systems

Jarrar¹,

Wakrime

Balouki³

2020

Complex Adapt Syst Model

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Complex adaptive systems provide a significant number of concepts such as reaction, interaction, adaptation, and evolution. In general, these concepts are modelled employing different techniques which give an inexplicit vision on the system. Therefore, all concepts must be carefully modelled using the same approach to avoid contradiction and guarantee system homogeneity and correctness. However, developing a computing system that includes all these concepts using the same approach is not an easy task and requires a perfect understanding of the system’s behaviour. In this paper, we contribute as stepwise towards proposing an approach to model the most important concepts of complex adaptive systems while ensuring homogeneity and the correctness of models. For this aim, we present five standard agent-based models formalizing agent properties, reaction, interaction, adaptation, and evolution. These models are adapted to all cases of complex adaptive systems since they include an abstract description of these concepts. To implement our approach formally, we choose the Event-B method due to the strong assurance of bugs’ absence that it guarantees. Besides, it supports horizontal and vertical refinement which facilitates the specification process. Furthermore, the approach of this paper addresses the very abstract level of modelling which expand the use of this approach to other formal methods and tools.

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Section: Adaptationmentioning

confidence: 99%

Formal approach to model complex adaptive computing systems

Jarrar¹,

Wakrime

Balouki³

2020

Complex Adapt Syst Model

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“…Autonomous unmanned systems like UAVs are controlled by software with self-adaptive planning methods [18], which decides the planning and subsequent actions in response to uncertainty in the dynamic environment. Although models of software and environment have been leveraged for automated adaptation in robotics software [19]- [21], little has been done to guarantee privacy preservation during UAVs' flights. In this work, we proposed a real-time self-adaptive planner which is responsible for task adaptation (e.g., taking an alternate path) and architectural adaptation (e.g., sensor reconfiguration).…”

Section: Related Workmentioning

confidence: 99%

Privacy-Aware UAV Flights through Self-Configuring Motion Planning

Luo

Jin

et al. 2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

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During flights, an unmanned aerial vehicle (UAV) may not be allowed to move across certain areas due to soft constraints such as privacy restrictions. Current methods on self-adaption focus mostly on motion planning such that the trajectory does not trespass predetermined restricted areas. When the environment is cluttered with uncertain obstacles, however, these motion planning algorithms are not flexible enough to find a trajectory that satisfies additional privacy-preserving requirements within a tight time budget during the flights. In this paper, we propose a privacy risk aware motion planning method through the reconfiguration of privacy-sensitive sensors. It minimises environmental impact by re-configuring the sensor during flight, while still guaranteeing the safety and energy hard constraints such as collision avoidance and timeliness. First, we formulate a model for assessing privacy risks of dynamically detected restricted areas. In case the UAV cannot find a feasible solution to satisfy both hard and soft constraints from the current configuration, our decision making method can then produce an optimal reconfiguration of the privacysensitive sensor with a more efficient trajectory. We evaluate the proposal through various simulations with different settings in a virtual environment and also validate the approach through real test flights on DJI Matrice 100 UAV.

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“…OC5) SCPS self-adaptation-While it makes a lot of sense for SCPS to adapt their configurations (and even their architectures) dynamically to changes in their environment or requirements [28], [29], building self-adaptation capabilities within SCPS is extremely challenging due to the multiple concerns that these systems need to consider. It has taken the research community the best of two decades to explore and advance self-adaptive software systems, and, while this research is relevant to SCPS [30], it needs to be considerably extended before it can address the non-"cyber" aspects of these systems.…”

Section: Oc2) Ensuring the Accuracy Of Stochastic Models Of Scps-mentioning

confidence: 99%

Socio-Cyber-Physical Systems: Models, Opportunities, Open Challenges

Călinescu¹,

Cámara

Paterson³

2019

2019 IEEE/ACM 5th International Workshop on Software Engineering for Smart Cyber-Physical Systems (SEsCPS)

Self Cite

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Almost without exception, cyber-physical systems operate alongside, for the benefit of, and supported by humans. Unsurprisingly, disregarding their social aspects during development and operation renders these systems ineffective. In this paper, we explore approaches to modelling and reasoning about the human involvement in socio-cyber-physical systems (SCPS). To provide an unbiased perspective, we describe both the opportunities afforded by the presence of human agents, and the challenges associated with ensuring that their modelling is sufficiently accurate to support decision making during SCPS development and, if applicable, at run-time. Using SCPS examples from emergency management and assisted living, we illustrate how recent advances in stochastic modelling, analysis and synthesis can be used to exploit human observations about the impact of natural and man-made disasters, and to support the efficient provision of assistive care.

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Model-Based Adaptation for Robotics Software

Cited by 20 publications

References 6 publications

Formal approach to model complex adaptive computing systems

Formal approach to model complex adaptive computing systems

Privacy-Aware UAV Flights through Self-Configuring Motion Planning

Socio-Cyber-Physical Systems: Models, Opportunities, Open Challenges

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