Reconfigurable Motion Planning and Control in Obstacle Cluttered Environments under Timed Temporal Tasks

Verginis, Christos K.; Vrohidis, Constantinos; Bechlioulis, Charalampos P.; Kyriakopoulos, Kostas J.; Dimarogonas, Dimos V.

doi:10.1109/icra.2019.8794000

Cited by 18 publications

(10 citation statements)

References 32 publications

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“…We use metric temporal logic (MTL) formulas to specify the expected control outcomes such as "the deaths from the infection should never exceed one thousand per day within the next three months" or "the population immune from the disease should eventually exceed 200 thousand within the next 100 to 120 days". Such temporal logic formulas have been used as high-level knowledge or specifications in many applications in artificial intelligence [8], robotic control [9], power systems [10], etc.…”

Section: Introductionmentioning

confidence: 99%

Control strategies for COVID-19 epidemic with vaccination, shield immunity and quarantine: A metric temporal logic approach

Topcu

2021

PLoS ONE

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Ever since the outbreak of the COVID-19 epidemic, various public health control strategies have been proposed and tested against the coronavirus SARS-CoV-2. We study three specific COVID-19 epidemic control models: the susceptible, exposed, infectious, recovered (SEIR) model with vaccination control; the SEIR model with shield immunity control; and the susceptible, un-quarantined infected, quarantined infected, confirmed infected (SUQC) model with quarantine control. We express the control requirement in metric temporal logic (MTL) formulas (a type of formal specification languages) which can specify the expected control outcomes such as “the deaths from the infection should never exceed one thousand per day within the next three months” or “the population immune from the disease should eventually exceed 200 thousand within the next 100 to 120 days”. We then develop methods for synthesizing control strategies with MTL specifications. To the best of our knowledge, this is the first paper to systematically synthesize control strategies based on the COVID-19 epidemic models with formal specifications. We provide simulation results in three different case studies: vaccination control for the COVID-19 epidemic with model parameters estimated from data in Lombardy, Italy; shield immunity control for the COVID-19 epidemic with model parameters estimated from data in Lombardy, Italy; and quarantine control for the COVID-19 epidemic with model parameters estimated from data in Wuhan, China. The results show that the proposed synthesis approach can generate control inputs such that the time-varying numbers of individuals in each category (e.g., infectious, immune) satisfy the MTL specifications. The results also show that early intervention is essential in mitigating the spread of COVID-19, and more control effort is needed for more stringent MTL specifications. For example, based on the model in Lombardy, Italy, achieving less than 100 deaths per day and 10000 total deaths within 100 days requires 441.7% more vaccination control effort than achieving less than 1000 deaths per day and 50000 total deaths within 100 days.

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Section: Introductionmentioning

confidence: 99%

Control strategies for COVID-19 epidemic with vaccination, shield immunity and quarantine: A metric temporal logic approach

Topcu

2021

PLoS ONE

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“…The works of [30], [31] consider cooperative planning of a multiagent system (MAS) with MITL specifications and the work of [34] further investigates MITL planning of a MAS subject to intermittent communication. When considering dynamic environments, MITL with probabilistic distributions (MITLD) is developed in [33] to express time-sensitive missions, and a Reconfigurable algorithm is developed in [32]. However, the aforementioned works assume that the desired MTIL specifications are always feasible for the robotic system.…”

Section: Introductionmentioning

confidence: 99%

Online Motion Planning with Soft Metric Interval Temporal Logic in Unknown Dynamic Environment

Li,

Cai,

Xiao

et al. 2021

Preprint

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Motion planning of an autonomous system with high-level specifications has wide applications. However, research of formal languages involving timed temporal logic is still under investigation. Furthermore, many existing results rely on a key assumption that user-specified tasks are feasible in the given environment. Challenges arise when the operating environment is dynamic and unknown since the environment can be found prohibitive, leading to potentially conflicting tasks where pre-specified timed missions cannot be fully satisfied. Such issues become even more challenging when considering timed requirements. To address these challenges, this work proposes a control framework that considers hard constraints to enforce safety requirements and soft constraints to enable task relaxation. The metric interval temporal logic (MITL) specifications are employed to deal with time-bound constraints. By constructing a relaxed timed product automaton, an online motion planning strategy is synthesized with a receding horizon controller to generate policies, achieving multiple objectives in decreasing order of priority 1) formally guarantee the satisfaction of hard safety constraints; 2) mostly fulfill soft timed tasks; and 3) collect time-varying rewards as much as possible. Another novelty of the relaxed structure is to consider violations of both time and tasks for infeasible cases. Simulation results are provided to validate the proposed approach.

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“…Email: {xiaomingduan.zju@gmail.com}. [1], robotics [2], power systems [3], etc. On the agentlevel, temporal logic formulas can express specifications for people in both indoor and outdoor spaces to obey the pandemic requirements (e.g., social distancing requirements).…”

Section: Introductionmentioning

confidence: 99%

Robust Pandemic Control Synthesis with Formal Specifications: A Case Study on COVID-19 Pandemic

Duan

2021

2021 60th IEEE Conference on Decision and Control (CDC)

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Pandemics can bring a range of devastating consequences to public health and the world economy. Identifying the most effective control strategies has been the imperative task all around the world. Various public health control strategies have been proposed and tested against pandemic diseases (e.g., . We study two specific pandemic control models: the susceptible, exposed, infectious, recovered (SEIR) model with vaccination control; and the SEIR model with shield immunity control. We express the pandemic control requirement in metric temporal logic (MTL) formulas. We then develop an iterative approach for synthesizing the optimal control strategies with MTL specifications. We provide simulation results in two different scenarios for robust control of the COVID-19 pandemic: one for vaccination control, and another for shield immunity control, with the model parameters estimated from data in Lombardy, Italy. The results show that the proposed synthesis approach can generate control inputs such that the time-varying numbers of individuals in each category (e.g., infectious, immune) satisfy the MTL specifications with robustness against initial state and parameter uncertainties.

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Reconfigurable Motion Planning and Control in Obstacle Cluttered Environments under Timed Temporal Tasks

Cited by 18 publications

References 32 publications

Control strategies for COVID-19 epidemic with vaccination, shield immunity and quarantine: A metric temporal logic approach

Control strategies for COVID-19 epidemic with vaccination, shield immunity and quarantine: A metric temporal logic approach

Online Motion Planning with Soft Metric Interval Temporal Logic in Unknown Dynamic Environment

Robust Pandemic Control Synthesis with Formal Specifications: A Case Study on COVID-19 Pandemic

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