Temporal logic motion planning using POMDPs with parity objectives

Svoreňová, Mária; Chmelík, Martin; Leahy, Kevin; Enişer, Hasan Ferit; Chatterjee, Krishnendu; Černá, Ivana; Belta, Călin

doi:10.1145/2728606.2728617

Cited by 25 publications

(29 citation statements)

References 15 publications

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“…Such a discrete planner can be used to satisfy complex objectives such as coverage, safety, and reachability. The design of discrete planners is widely studied in the literature [12,14,32,33] and is not the focus of this paper. Instead, we are interested in addressing the problem of converting the planner's discrete commands to continuous control signals, as stated below:…”

Section: Hybrid Control Problemmentioning

confidence: 99%

“…Such a discrete planner can be used to satisfy complex objectives such as coverage, safety, and reachability. The design of discrete planners is widely studied in the literature [12, 14, 32, 33] and is not the focus of this paper. Instead, we are interested in addressing the problem of converting the planner's discrete commands to continuous control signals, as stated below: Problem For the multi‐affine systems described in (1) and a discrete planner G in (10), design a hybrid controller to generate jumpless control signals,

u false(t false)

, so that the trajectories of the controlled system,

x false(t false)

, follow the commands of the discrete planner G , while respecting the velocity constraint

| \dot{x} | \leq M_{v}

.…”

Section: Problem Formulationmentioning

confidence: 99%

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Design of smooth hybrid controllers for a class of non‐linear systems

Shamgah

Tadewos

Karimoddini

2020

IET Control Theory & Appl

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Symbolic planning techniques rely on abstract information about a continuous system to design a discrete planner to satisfy desired high-level objectives. However, applying the generated discrete commands of the discrete planner to the original system may face several challenges, including real-time implementation, preserving the properties of high-level objectives in the continuous domain, and issues such as discontinuity in control signals that may physically harm the system. To address these issues and challenges, the authors proposed a novel hybrid control structure for systems with non-linear multi-affine dynamics over rectangular partitions. In the proposed framework, a discrete planner can be separately designed to achieve high-level specifications. Then, the proposed hybrid controller generates jumpless continuous control signals to drive the system over the partitioned space executing the discrete commands of the planner. The hybrid controller generates continuous signals in realtime while respecting the dynamics of the system and preserving the desired objectives of the high-level plan. The design process is described in detail and the existence and uniqueness of the proposed solution are investigated. Finally, several case studies are provided to verify the effectiveness of the developed technique.

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Section: Hybrid Control Problemmentioning

confidence: 99%

“…Such a discrete planner can be used to satisfy complex objectives such as coverage, safety, and reachability. The design of discrete planners is widely studied in the literature [12, 14, 32, 33] and is not the focus of this paper. Instead, we are interested in addressing the problem of converting the planner's discrete commands to continuous control signals, as stated below: Problem For the multi‐affine systems described in (1) and a discrete planner G in (10), design a hybrid controller to generate jumpless control signals,

u false(t false)

, so that the trajectories of the controlled system,

x false(t false)

, follow the commands of the discrete planner G , while respecting the velocity constraint

| \dot{x} | \leq M_{v}

.…”

Section: Problem Formulationmentioning

confidence: 99%

Design of smooth hybrid controllers for a class of non‐linear systems

Shamgah

Tadewos

Karimoddini

2020

IET Control Theory & Appl

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“…IV and V in C++. In this section, we demonstrate their use on a case study motivated by examples in [4], [18]. All executions were performed on Mac OS X 10.10.3 with 2.6 GHz Intel Core i5 processor and 8 GB 1600 MHz DDR3 memory.…”

Section: Case Studymentioning

confidence: 99%

Optimal observation mode scheduling for systems under temporal constraints

Tesarova

Svoreňová

Barnat

et al. 2016

2016 American Control Conference (ACC)

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Autonomous control systems use various sensors to decrease the amount of uncertainty under which they operate. While providing partial observation of the current state of the system, sensors require resources such as energy, time and communication. We consider discrete systems with non-deterministic transitions and multiple observation modes.The observation modes provide different information about the states of the system and are associated with non-negative costs. We consider two control problems. First, we aim to construct a control and observation mode switching strategy that guarantees satisfaction of a finite-time temporal property given as a formula of syntactically co-safe fragment of LTL (scLTL) and at the same time, minimizes the worst-case cost accumulated until the point of satisfaction. Second, the bounded version of the problem is considered, where the temporal property must be satisfied within given finite time bound. We present correct and optimal solutions to both problems and demonstrate their usability on a case study motivated by robotic applications.The authors are with

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“…Also, both partially observable Markov decision processes, e.g. [29,32], and stochastic games, e.g. [8,31] have been used in conjunction with temporal logic for controller synthesis of autonomous agents.…”

Section: Introductionmentioning

confidence: 99%

Strategy Synthesis for Autonomous Agents Using PRISM

Giaquinta

Hoffmann

Ireland

et al. 2018

Lecture Notes in Computer Science

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Abstract. We present probabilistic models for autonomous agent search and retrieve missions derived from Simulink models for an Unmanned Aerial Vehicle (UAV) and show how probabilistic model checking and the probabilistic model checker PRISM can be used for optimal controller generation. We introduce a sequence of scenarios relevant to UAVs and other autonomous agents such as underwater and ground vehicles. For each scenario we demonstrate how it can be modelled using the PRISM language, give model checking statistics and present the synthesised optimal controllers. We conclude with a discussion of the limitations when using probabilistic model checking and PRISM in this context and what steps can be taken to overcome them. In addition, we consider how the controllers can be returned to the UAV and adapted for use on larger search areas.

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Temporal logic motion planning using POMDPs with parity objectives

Cited by 25 publications

References 15 publications

Design of smooth hybrid controllers for a class of non‐linear systems

Design of smooth hybrid controllers for a class of non‐linear systems

Optimal observation mode scheduling for systems under temporal constraints

Strategy Synthesis for Autonomous Agents Using PRISM

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